KaaIoT

About Our Client

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role

We are looking for a Senior Software Engineer to build and operate production AI agent and search services on top of a large-scale data platform. This is hands-on work at the intersection of distributed backend engineering and applied AI: multi-agent workflows, tool-execution infrastructure, retrieval and relevance, and integrations with multiple LLM providers — all running as real, customer-facing production services with the reliability expectations that implies.

Responsibilities

• Design and implement scalable multi-agent workflows (including conversation state), tool-execution infrastructure, and data-aware tools working with catalogs, schemas, lineage, SQL, jobs, semantic metadata, data preparation, and visualizations
• Build search and retrieval capabilities with OpenSearch or equivalent — indexing, relevance tuning, hybrid keyword + vector search
• Integrate multiple LLM/model providers with secure configuration and graceful degradation
• Develop APIs and event contracts across REST, streaming/SSE, gRPC, protobuf, and SDKs, including UI integrations
• Operate, monitor, and improve production services — service health, logs, metrics, traces, search-cluster health, latency, and error rates; participate in the team's production-support model
• Investigate incidents, drive root-cause analysis, and ship durable fixes
• Design for permissions, tool approvals, multi-tenancy, and customer-data governance
• Maintain dependencies, apply security fixes, and reduce tech debt; produce designs, tests, runbooks, and documentation; lead technical discussions and review code

Required Qualifications

• B.S. or M.S. in Computer Science, Computer Engineering, or a related field — or equivalent practical experience
• 7+ years of relevant experience, or equivalent demonstrated senior-level impact
• Strong Java software engineering skills
• Strong grasp of concurrency, data structures, API design, testing, maintainability, and backward compatibility
• Solid background in distributed systems, microservices, cloud services, or data-intensive backends
• Hands-on experience with search technologies — OpenSearch, Elasticsearch, or Lucene — including vector search, embeddings, or relevance systems
• Experience building LLM applications, agent/tool workflows, RAG systems, or model-provider integrations
• Strong production instincts: diagnosing failures via logs, metrics, and traces; designing for fault tolerance, retries, cancellation, and recovery
• SQL and familiarity with data platform concepts: catalogs, metadata, schemas, governance, lineage
• Comfort leading ambiguous, cross-service work with clear stakeholder communication and strong written documentation
• Comfortable with AI-assisted development workflows — using modern AI tools productively while critically validating their output
• English Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team
• Availability to work EU business hours shifted 2–3 hours later for daily overlap with US West Coast mornings

Desired Skills

• LangChain4j or similar agent frameworks
• Python for AI services, evaluation harnesses, or sandboxed execution
• React and TypeScript
• gRPC, protobuf, Quarkus, Kubernetes, MongoDB, KV stores, event-driven architectures
• Apache Arrow, Apache Iceberg, OpenLineage, semantic layers, or data-governance systems
• AI quality evaluation: LLM-as-judge, model benchmarking, production AI metrics
• OpenSearch operations: index lifecycle management, relevance tuning, incident response
• Open-source contributions

Details

• Engagement: Long-term contract
• Location: Europe (EU / EEA / UK), remote
• Working hours: EU business hours, shifted 2–3 hours later for daily overlap with the US West Coast team

About Our Client

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role

We are looking for a Senior Software Engineer for the data catalog and enterprise data management layer of a large-scale lakehouse platform — the services that automate data ingestion and autonomously optimize Apache Iceberg tables. You will own features through the full development cycle, from design through deployment, in a multithreaded, distributed environment where scalability, performance, and always-on availability are the baseline expectations.

This is a systems-level, backend engineering role focused on data infrastructure internals — not application development or CRUD services.

Responsibilities

• Own the full software development cycle — inception, design, development, testing, deployment — for catalog and data-management services
• Build and operate services for automated ingestion and autonomous optimization of Apache Iceberg tables
• Reason about concurrency and parallelization to deliver scalability and performance in multithreaded, distributed systems
• Drive performance tuning and system-efficiency improvements
• Work with Apache Foundation open-source projects, contributing upstream where agreed
• Participate in code and design reviews, upholding a high engineering bar
• Collaborate with product managers, support teams, and solution architects on feature requests and design updates
• Partner with US-based engineering leads on technical decisions

Required Qualifications

• B.S., M.S., or PhD in Computer Science or a related field
• 5+ years of software engineering experience, preferably focused on database systems or related fields
• Strong object-oriented programming skills in Java or C++
• Solid grounding in data structures and algorithms
• Hands-on experience with multithreaded and asynchronous programming patterns for scalable, performant systems
• A passion for engineering quality — zero-downtime upgrades, availability, resiliency, and uptime as first-class concerns
• Comfort with a fast-moving environment; strong ownership; the confidence to defend a technical position and the openness to be mentored
• Comfortable with AI-assisted development workflows — using modern AI tools productively while critically validating their output
• English Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team
• Availability to work EU business hours shifted 2–3 hours later for daily overlap with US West Coast mornings

Desired Skills

• Database internals and query planning
• Distributed systems: concurrency control, data replication, storage systems
• Apache Iceberg or other open table formats (Delta Lake, Hudi)
• Messaging systems: Kafka, NATS, or cloud pub/sub services
• Contributions to open-source data infrastructure (Apache projects especially valued)

Details

• Engagement: Long-term contract
• Location: Europe (EU / EEA / UK), remote
• Working hours: EU business hours, shifted 2–3 hours later for daily overlap with the US West Coast team

About Our Client

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role

We are looking for a Senior Software Engineer for the connectivity stack of a large-scale data platform. The work spans three areas:

• Client connectivity — drivers and client libraries used by applications and BI tools
• Source connectivity — connectors to databases and data systems, including authentication, metadata discovery, and query/data pushdown, with certification and upgrade support
• Agent & service connectivity — tool interfaces and integrations for AI-agent access to the platform

Deep expertise in one of these areas is enough — you'll grow into the adjacent ones over time. This is a role for an engineer who cares about API and protocol stability, backward compatibility, and interoperability with the tools enterprises actually use. You will lead the design and delivery of substantial components, working within an established architecture alongside US-based engineering reviewers.

This is a systems-level, backend engineering role focused on drivers, protocols, and distributed services — not application development or CRUD services.

Responsibilities

• Lead the design and delivery of connectivity components — client drivers, source connectors, and service integrations — turning ambiguous initiatives into well-scoped, reviewable milestones
• Produce technical designs, explain architectural trade-offs, and surface compatibility, security, and delivery risks early
• Maintain backward compatibility and API/protocol stability; build compatibility, interoperability, and performance test suites
• Develop and maintain connectors for major BI tools, collaborating with the technology partners behind them
• Diagnose complex client/server, protocol, and distributed-system failures; drive root-cause analysis of customer-reported and escaped defects
• Improve diagnostics, logging, observability, and supportability of the connectivity stack
• Contribute upstream to open-source projects (e.g., Apache Arrow) where agreed
• Mentor engineers, participate in code and design reviews, and communicate progress and risks clearly across a distributed team

Required Qualifications

• B.S. or M.S. in Computer Science, Computer Engineering, or a related field — or equivalent practical experience
• 8+ years of production software engineering experience
• Deep proficiency in Java or C++, and the ability to work effectively in another systems/services language
• Experience designing and debugging APIs, protocols, client libraries, or distributed services
• Strong fundamentals: data structures, concurrency, asynchronous programming, networking, and failure handling
• A track record of comprehensive testing — unit, integration, compatibility, and performance
• Experience with production CI/CD, release processes, and engineering quality controls
• Working knowledge of SQL
• Comfortable with AI-assisted development workflows — using modern AI tools productively while critically validating their output
• Clear written and verbal communication in a distributed engineering environment; English Upper-Intermediate or higher (B2+)
• Availability to work EU business hours shifted 2–3 hours later for daily overlap with US West Coast mornings

Desired Skills

• JDBC, ODBC, ADBC, or database-driver development experience
• Apache Arrow (including Arrow Flight)
• SQL engines, databases, or data platforms
• Source-connector development for databases, warehouses, or SaaS systems
• MCP or agent-tool integrations
• OAuth, OIDC, TLS, and enterprise authentication flows
• Cross-platform native build, packaging, and release experience
• BI-tool interoperability (Power BI, Tableau) and partner collaboration
• Observability and production diagnostics
• Open-source contribution experience

Details

• Engagement: Long-term contract
• Location: Europe (EU / EEA / UK), remote
• Working hours: EU business hours, shifted 2–3 hours later for daily overlap with the US West Coast team

Level: Middle Engagement: Long-term contract Location: Europe (EU / EEA / UK), remote Working hours: EU business hours, shifted 2–3 hours later to ensure daily overlap with US West Coast (PST/PDT) mornings

About the Client

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role

We are looking for a Middle-level SDET to design and maintain automated tests for a large-scale distributed data platform. You will validate the correctness, performance, and reliability of the query engine, connectivity layer, and backend services across all major clouds.

This is a data-heavy, backend-focused role. We are not looking for web/UI QA engineers — the work centers on validating distributed query execution, data correctness at scale, connectivity drivers, and backend microservices.

Responsibilities

• Develop and maintain automated tests in Python / pytest for backend services, REST APIs, and distributed data components.
• Write end-to-end, integration, and regression tests covering SQL query execution, data correctness, and platform APIs.
• Support performance and load testing with JMeter, including workloads over JDBC / ODBC / Arrow Flight drivers.
• Validate data-intensive scenarios — query plans, result correctness across data sources, metadata consistency, and behavior under concurrency.
• Contribute to CI/CD test pipelines in Jenkins — configure, maintain, and troubleshoot.
• Provision and manage test environments in Kubernetes (GKE / EKS / AKS) across GCP, AWS, and Azure using Docker.
• Investigate failures across the stack — query engine, distributed services, drivers, infrastructure — and drive them to resolution with engineering.
• Collaborate with US-based developers on testability and quality gates.

Required Qualifications

• Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field.
• Programming: Strong proficiency in Python, including pytest, with a solid grasp of OOP and software design principles.
• SQL & Data: Strong SQL skills and solid understanding of how relational and analytical data systems work.
• Data-intensive testing experience: Hands-on experience testing data-intensive systems — query engines, ETL/ELT pipelines, streaming platforms, or analytical databases. Candidates with only web/UI QA backgrounds are not a fit.
• Testing experience: 3+ years in backend/system test automation or SDET roles.
• CI/CD & DevOps basics: Practical experience with Jenkins pipelines and deploying/maintaining test environments.
• Containers: Working knowledge of Docker and basic Kubernetes (running workloads, debugging pods, kubectl fluency).
• Cloud: Comfortable operating in at least one major cloud (GCP, AWS, or Azure).
• Version Control: Confident with Git / GitHub workflows.
• English: Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team.
• Availability: Able to work EU hours with a 2–3 hour shift toward US West Coast time to ensure daily overlap with the client team.

Desired Skills

• Experience testing REST APIs and backend microservices at scale.
• Familiarity with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines (e.g., Presto, Trino, or similar).
• Understanding of modern data lakehouse concepts, open table formats (Apache Iceberg), and data warehousing.
• Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight.
• Performance testing with JMeter or comparable load-testing tools.
• Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure.
• IaC tools such as Terraform.
• Understanding of query plan generation, query acceleration / materializations, and metadata integrity in distributed data systems.
  Please note: We can consider only candidates currently residing in the EU, EEA, or the UK

Level: Senior Engagement: Long-term contract Location: Europe (EU / EEA / UK), remote Working hours: EU business hours, shifted 2–3 hours later to ensure daily overlap with US West Coast (PST/PDT) mornings

About the Client

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role

We are looking for a Senior SDET to lead the design of automated test frameworks and testing strategy for a large-scale distributed data platform. You will own the quality of the query engine, connectivity layer, and backend services end-to-end — from framework architecture through CI/CD infrastructure across all major clouds — and mentor middle engineers on the team.

This is a data-heavy, backend-focused role. We are not looking for web/UI QA engineers — the work centers on validating distributed query execution, data correctness at scale, connectivity drivers, and backend microservices.

Responsibilities

• Architect, design, and evolve automated test frameworks in Python / pytest for backend services, REST APIs, and distributed data components.
• Define testing strategy for new features and platform components — coverage, risk assessment, and quality gates.
• Own end-to-end, integration, performance, and regression testing covering SQL query execution, data correctness at scale, and platform APIs.
• Lead performance and load testing efforts with JMeter, including workloads over JDBC / ODBC / Arrow Flight drivers.
• Design and validate large-scale data testing scenarios — query plans, result correctness across heterogeneous data sources, metadata consistency, and behavior under high concurrency.
• Own CI/CD test pipelines in Jenkins — architect, maintain, and continuously improve.
• Provision and manage test environments in Kubernetes (GKE / EKS / AKS) across GCP, AWS, and Azure using Docker; drive automation and reproducibility.
• Investigate complex, cross-layer failures and drive root-cause analysis with engineering.
• Mentor middle SDETs, review test designs, and set quality standards across the team.
• Partner with US-based development leads on shift-left practices, testability, and release readiness.

Required Qualifications

• Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field.
• Programming: Strong proficiency in Python, including pytest, with deep understanding of OOP, software design principles, and test framework architecture.
• SQL & Data: Advanced SQL skills and strong understanding of relational and analytical data systems, including query execution internals.
• Data-intensive testing experience: Demonstrated experience testing data-intensive systems — query engines, ETL/ELT pipelines, streaming platforms, or analytical databases. Candidates with only web/UI QA backgrounds are not a fit.
• Testing experience: 5+ years in backend/system test automation, with demonstrated ownership of test strategy and infrastructure.
• CI/CD & DevOps: Solid experience architecting and maintaining Jenkins pipelines and test environments.
• Containers & Orchestration: Strong working knowledge of Docker and Kubernetes (running workloads, debugging pods, deploying complex environments).
• Cloud: Hands-on experience with at least one major cloud (GCP, AWS, or Azure); exposure to more than one is a strong plus.
• Version Control: Confident with Git / GitHub workflows and code review practices.
• English: Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team.
• Availability: Able to work EU hours with a 2–3 hour shift toward US West Coast time to ensure daily overlap with the client team.
• Leadership: Prior experience mentoring engineers, defining test strategy, or leading a QA/SDET function.

Desired Skills

• Deep experience testing REST APIs and backend microservices at scale.
• Hands-on with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines (e.g., Presto, Trino, or similar).
• Strong understanding of modern data lakehouse concepts, open table formats (Apache Iceberg), and data warehousing.
• Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight.
• Performance testing with JMeter or comparable load-testing tools at production scale.
• Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure.
• IaC tools such as Terraform.
• Deep understanding of query plan generation, query acceleration / materializations, and metadata integrity in distributed data systems.
• Prior experience leading a QA/SDET function in a data-platform or database engineering environment.
  Please note: We can consider only candidates currently residing in the EU, EEA, or the UK.

Level: Senior Engagement: Long-term contract Location: Europe (EU / EEA / UK), remote Working hours: EU business hours, shifted 2–3 hours later to ensure daily overlap with US West Coast (PST/PDT) mornings

About the Client

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role

We are looking for a Senior Software Engineer to design, build, and own significant components of the core query engine of a large-scale distributed data platform. You will lead work across query planning, optimization, and execution — driving architectural decisions, mentoring middle engineers, and pushing the platform's performance and scalability boundaries across all major clouds.

This is a systems-level, backend engineering role focused on distributed data processing internals — not application development or CRUD services.

Responsibilities

• Architect, design, and implement significant components of the query engine — planner, optimizer, execution operators, memory management, and data access layers.
• Write and review high-quality, performance-critical code in Java and/or C++.
• Own end-to-end delivery of features from technical design through production rollout.
• Drive performance optimization work — profiling, benchmarking, and eliminating bottlenecks in latency- and throughput-sensitive paths.
• Integrate deeply with columnar formats, open table formats, and connectivity drivers.
• Mentor middle engineers, lead code reviews, and set technical standards for the team.
• Contribute to CI/CD architecture and quality processes across Jenkins, containerization, and multi-cloud deployment (GCP, AWS, Azure via Kubernetes / Docker).
• Debug complex, cross-layer issues spanning query planning, distributed execution, memory management, and I/O.
• Partner with US-based engineering leads on design reviews, architectural decisions, and roadmap execution.

Required Qualifications

• Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field.
• Programming: Strong proficiency in Java or C++, with deep understanding of OOP, systems design, memory management, and concurrency. Candidates strong in both are especially valued.
• SQL & Data: Advanced SQL skills and strong understanding of query execution internals — planning, optimization, and operator implementation.
• Data processing systems experience: Demonstrated experience building or extending data processing systems — query engines, distributed databases, ETL/ELT frameworks, or analytical platforms.
• Engineering experience: 5+ years in backend/systems software engineering, with a track record of owning significant components.
• CI/CD & DevOps: Solid experience with Jenkins and modern engineering workflows.
• Containers & Orchestration: Strong working knowledge of Docker and Kubernetes.
• Cloud: Hands-on experience with at least one major cloud (GCP, AWS, or Azure); exposure to more than one is a strong plus.
• Version Control: Confident with Git / GitHub workflows and rigorous code review practices.
• English: Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team.
• Availability: Able to work EU hours with a 2–3 hour shift toward US West Coast time to ensure daily overlap with the client team.
• Leadership: Prior experience mentoring engineers, leading technical designs, or owning components end-to-end.

Desired Skills

• Deep experience with Apache Arrow (columnar in-memory format).
• Hands-on experience with Apache Calcite (SQL parsing, planning, optimization framework).
• Experience with Gandiva or LLVM-based expression compilation and code generation.
• Experience with open table formats — Apache Iceberg, Delta Lake, or Hudi.
• Deep familiarity with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines (e.g., Presto, Trino, or similar).
• Deep understanding of query planning, optimization (cost-based, rule-based), and execution internals.
• Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight.
• Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure.
• IaC tools such as Terraform.
• Track record of performance optimization at the systems level — profiling, vectorization, cache/memory-conscious design.
• Prior experience contributing to open-source data infrastructure projects.
  Please note: We can consider only candidates currently residing in the EU, EEA, or the UK

Level: Middle Engagement: Long-term contract Location: Europe (EU / EEA / UK), remote Working hours: EU business hours, shifted 2–3 hours later to ensure daily overlap with US West Coast (PST/PDT) mornings

About the Client

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role

We are looking for a Middle-level Software Engineer to work on the core query engine of a large-scale distributed data platform. You will develop features across query planning, optimization, and execution, contribute to performance-critical components, and help evolve the platform's ability to process massive analytical workloads across heterogeneous data sources.

This is a systems-level, backend engineering role focused on distributed data processing internals — not application development or CRUD services.

Responsibilities

• Develop and maintain features across the query engine — planning, optimization, execution, and data access layers.
• Write high-quality, performance-conscious code in Java and/or C++.
• Work with SQL semantics, query plans, and execution operators over large-scale distributed data.
• Integrate with columnar formats, open table formats, and connectivity drivers used across the platform.
• Contribute to CI/CD pipelines and automated testing — participate in build, test, and release workflows in Jenkins.
• Deploy and validate work in Kubernetes (GKE / EKS / AKS) across GCP, AWS, and Azure using Docker.
• Debug complex issues spanning query planning, distributed execution, memory management, and I/O.
• Collaborate closely with US-based engineering teams on design reviews, code reviews, and technical decisions.

Required Qualifications

• Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field.
• Programming: Strong proficiency in Java or C++, with solid OOP and software design fundamentals. Candidates comfortable with both are especially valued.
• SQL & Data: Strong SQL skills and solid understanding of relational and analytical data systems, including query execution concepts.
• Data processing systems experience: Hands-on experience with data processing systems — query engines, distributed databases, ETL/ELT frameworks, or analytical platforms.
• Engineering experience: 3+ years in backend/systems software engineering.
• CI/CD & DevOps basics: Practical experience with Jenkins pipelines and modern development workflows.
• Containers: Working knowledge of Docker and basic Kubernetes (running workloads, debugging pods, kubectl fluency).
• Cloud: Comfortable operating in at least one major cloud (GCP, AWS, or Azure).
• Version Control: Confident with Git / GitHub workflows.
• English: Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team.
• Availability: Able to work EU hours with a 2–3 hour shift toward US West Coast time to ensure daily overlap with the client team.

Desired Skills

• Experience with Apache Arrow (columnar in-memory format).
• Familiarity with Apache Calcite (SQL parsing, planning, optimization framework).
• Exposure to Gandiva or LLVM-based expression compilation.
• Experience with open table formats — Apache Iceberg, Delta Lake, or Hudi.
• Familiarity with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines (e.g., Presto, Trino, or similar).
• Understanding of query planning, optimization, and execution internals.
• Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight.
• Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure.
• IaC tools such as Terraform.
• Experience with performance profiling and optimization of latency-sensitive systems.
  Please note: We can consider only candidates currently residing in the EU, EEA, or the UK.
  Please note: We can consider only candidates currently residing in the EU, EEA, or the UK

Level: Middle Engagement: Long-term contract Location: Europe (EU / EEA / UK), remote Working hours:EU business hours, shifted 2–3 hours later to ensure daily overlap with US West Coast (PST/PDT) mornings

ABOUT THE CLIENT

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

ABOUT THE ROLE

We are looking for a Middle-level Software Engineer to work on the core query engine of a large-scale distributed data platform. You will develop features across query planning, optimization, and execution, contribute to performance-critical components, and help evolve the platform's ability to process massive analytical workloads across heterogeneous data sources.

This is a systems-level, backend engineering role focused on distributed data processing internals — not application development or CRUD services.

RESPONSIBILITIES

• Develop and maintain features across the query engine — planning, optimization, execution, and data access layers.
• Write high-quality, performance-conscious code in Java and/or C++.
• Work with SQL semantics, query plans, and execution operators over large-scale distributed data.
• Integrate with columnar formats, open table formats, and connectivity drivers used across the platform.
• Contribute to CI/CD pipelines and automated testing — participate in build, test, and release workflows in Jenkins.
• Deploy and validate work in Kubernetes (GKE / EKS / AKS) across GCP, AWS, and Azure using Docker.
• Debug complex issues spanning query planning, distributed execution, memory management, and I/O.
• Collaborate closely with US-based engineering teams on design reviews, code reviews, and technical decisions.

REQUIRED QUALIFICATIONS

• Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field.
• Programming: Strong proficiency in Java or C++, with solid OOP and software design fundamentals. Candidates comfortable with both are especially valued.
• SQL & Data: Strong SQL skills and solid understanding of relational and analytical data systems, including query execution concepts.
• Data processing systems experience: Hands-on experience with data processing systems — query engines, distributed databases, ETL/ELT frameworks, or analytical platforms.
• Engineering experience: 3+ years in backend/systems software engineering.
• CI/CD & DevOps basics: Practical experience with Jenkins pipelines and modern development workflows.
• Containers: Working knowledge of Docker and basic Kubernetes (running workloads, debugging pods, kubectl fluency).
• Cloud: Comfortable operating in at least one major cloud (GCP, AWS, or Azure).
• Version Control: Confident with Git / GitHub workflows.
• English: Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team.
• Availability: Able to work EU hours with a 2–3 hour shift toward US West Coast time to ensure daily overlap with the client team.

DESIRED SKILLS

• Experience with Apache Arrow (columnar in-memory format).
• Familiarity with Apache Calcite (SQL parsing, planning, optimization framework).
• Exposure to Gandiva or LLVM-based expression compilation.
• Experience with open table formats — Apache Iceberg, Delta Lake, or Hudi.
• Familiarity with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines(e.g., Presto, Trino, or similar).
• Understanding of query planning, optimization, and execution internals.
• Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight.
• Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure.
• IaC tools such as Terraform.
• Experience with performance profiling and optimization of latency-sensitive systems.
• Please note: We can consider only candidates currently residing in the EU, EEA, or the UK.

Level: Senior Engagement: Long-term contract Location: Europe (EU / EEA / UK), remote Working hours:EU business hours, shifted 2–3 hours later to ensure daily overlap with US West Coast (PST/PDT) mornings

ABOUT THE CLIENT

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

ABOUT THE ROLE

We are looking for a Senior Software Engineer to design, build, and own significant components of the core query engine of a large-scale distributed data platform. You will lead work across query planning, optimization, and execution — driving architectural decisions, mentoring middle engineers, and pushing the platform's performance and scalability boundaries across all major clouds.

This is a systems-level, backend engineering role focused on distributed data processing internals — not application development or CRUD services.

RESPONSIBILITIES

• Architect, design, and implement significant components of the query engine — planner, optimizer, execution operators, memory management, and data access layers.
• Write and review high-quality, performance-critical code in Java and/or C++.
• Own end-to-end delivery of features from technical design through production rollout.
• Drive performance optimization work — profiling, benchmarking, and eliminating bottlenecks in latency- and throughput-sensitive paths.
• Integrate deeply with columnar formats, open table formats, and connectivity drivers.
• Mentor middle engineers, lead code reviews, and set technical standards for the team.
• Contribute to CI/CD architecture and quality processes across Jenkins, containerization, and multi-cloud deployment (GCP, AWS, Azure via Kubernetes / Docker).
• Debug complex, cross-layer issues spanning query planning, distributed execution, memory management, and I/O.
• Partner with US-based engineering leads on design reviews, architectural decisions, and roadmap execution.

REQUIRED QUALIFICATIONS

• Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field.
• Programming: Strong proficiency in Java or C++, with deep understanding of OOP, systems design, memory management, and concurrency. Candidates strong in both are especially valued.
• SQL & Data: Advanced SQL skills and strong understanding of query execution internals — planning, optimization, and operator implementation.
• Data processing systems experience: Demonstrated experience building or extending data processing systems — query engines, distributed databases, ETL/ELT frameworks, or analytical platforms.
• Engineering experience: 5+ years in backend/systems software engineering, with a track record of owning significant components.
• CI/CD & DevOps: Solid experience with Jenkins and modern engineering workflows.
• Containers & Orchestration: Strong working knowledge of Docker and Kubernetes.
• Cloud: Hands-on experience with at least one major cloud (GCP, AWS, or Azure); exposure to more than one is a strong plus.
• Version Control: Confident with Git / GitHub workflows and rigorous code review practices.
• English: Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team.
• Availability: Able to work EU hours with a 2–3 hour shift toward US West Coast time to ensure daily overlap with the client team.
• Leadership: Prior experience mentoring engineers, leading technical designs, or owning components end-to-end.

DESIRED SKILLS

• Deep experience with Apache Arrow (columnar in-memory format).
• Hands-on experience with Apache Calcite (SQL parsing, planning, optimization framework).
• Experience with Gandiva or LLVM-based expression compilation and code generation.
• Experience with open table formats — Apache Iceberg, Delta Lake, or Hudi.
• Deep familiarity with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines (e.g., Presto, Trino, or similar).
• Deep understanding of query planning, optimization (cost-based, rule-based), and execution internals.
• Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight.
• Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure.
• IaC tools such as Terraform.
• Track record of performance optimization at the systems level — profiling, vectorization, cache/memory-conscious design.
• Prior experience contributing to open-source data infrastructure projects.
• Please note: We can consider only candidates currently residing in the EU, EEA, or the UK

Level: Middle Engagement: Long-term contract Location: Europe (EU / EEA / UK), remote Working hours:EU business hours, shifted 2–3 hours later to ensure daily overlap with US West Coast (PST/PDT) mornings

ABOUT THE CLIENT

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

ABOUT THE ROLE

We are looking for a Middle-level SDET to design and maintain automated tests for a large-scale distributed data platform. You will validate the correctness, performance, and reliability of the query engine, connectivity layer, and backend services across all major clouds.

This is a data-heavy, backend-focused role. We are not looking for web/UI QA engineers — the work centers on validating distributed query execution, data correctness at scale, connectivity drivers, and backend microservices.

RESPONSIBILITIES

• Develop and maintain automated tests in Python / pytest for backend services, REST APIs, and distributed data components.
• Write end-to-end, integration, and regression tests covering SQL query execution, data correctness, and platform APIs.
• Support performance and load testing with JMeter, including workloads over JDBC / ODBC / Arrow Flightdrivers.
• Validate data-intensive scenarios — query plans, result correctness across data sources, metadata consistency, and behavior under concurrency.
• Contribute to CI/CD test pipelines in Jenkins — configure, maintain, and troubleshoot.
• Provision and manage test environments in Kubernetes (GKE / EKS / AKS) across GCP, AWS, and Azure using Docker.
• Investigate failures across the stack — query engine, distributed services, drivers, infrastructure — and drive them to resolution with engineering.
• Collaborate with US-based developers on testability and quality gates.

REQUIRED QUALIFICATIONS

• Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field.
• Programming: Strong proficiency in Python, including pytest, with a solid grasp of OOP and software design principles.
• SQL & Data: Strong SQL skills and solid understanding of how relational and analytical data systems work.
• Data-intensive testing experience: Hands-on experience testing data-intensive systems — query engines, ETL/ELT pipelines, streaming platforms, or analytical databases. Candidates with only web/UI QA backgrounds are not a fit.
• Testing experience: 3+ years in backend/system test automation or SDET roles.
• CI/CD & DevOps basics: Practical experience with Jenkins pipelines and deploying/maintaining test environments.
• Containers: Working knowledge of Docker and basic Kubernetes (running workloads, debugging pods, kubectl fluency).
• Cloud: Comfortable operating in at least one major cloud (GCP, AWS, or Azure).
• Version Control: Confident with Git / GitHub workflows.
• English: Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team.
• Availability: Able to work EU hours with a 2–3 hour shift toward US West Coast time to ensure daily overlap with the client team.

DESIRED SKILLS

• Experience testing REST APIs and backend microservices at scale.
• Familiarity with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines(e.g., Presto, Trino, or similar).
• Understanding of modern data lakehouse concepts, open table formats (Apache Iceberg), and data warehousing.
• Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight.
• Performance testing with JMeter or comparable load-testing tools.
• Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure.
• IaC tools such as Terraform.
• Understanding of query plan generation, query acceleration / materializations, and metadata integrity in distributed data systems.
• Please note: We can consider only candidates currently residing in the EU, EEA, or the UK

Level: Senior Engagement: Long-term contract Location: Europe (EU / EEA / UK), remote Working hours:EU business hours, shifted 2–3 hours later to ensure daily overlap with US West Coast (PST/PDT) mornings

ABOUT THE CLIENT

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

ABOUT THE ROLE

We are looking for a Senior SDET to lead the design of automated test frameworks and testing strategy for a large-scale distributed data platform. You will own the quality of the query engine, connectivity layer, and backend services end-to-end — from framework architecture through CI/CD infrastructure across all major clouds — and mentor middle engineers on the team.

This is a data-heavy, backend-focused role. We are not looking for web/UI QA engineers — the work centers on validating distributed query execution, data correctness at scale, connectivity drivers, and backend microservices.

RESPONSIBILITIES

• Architect, design, and evolve automated test frameworks in Python / pytest for backend services, REST APIs, and distributed data components.
• Define testing strategy for new features and platform components — coverage, risk assessment, and quality gates.
• Own end-to-end, integration, performance, and regression testing covering SQL query execution, data correctness at scale, and platform APIs.
• Lead performance and load testing efforts with JMeter, including workloads over JDBC / ODBC / Arrow Flightdrivers.
• Design and validate large-scale data testing scenarios — query plans, result correctness across heterogeneous data sources, metadata consistency, and behavior under high concurrency.
• Own CI/CD test pipelines in Jenkins — architect, maintain, and continuously improve.
• Provision and manage test environments in Kubernetes (GKE / EKS / AKS) across GCP, AWS, and Azure using Docker; drive automation and reproducibility.
• Investigate complex, cross-layer failures and drive root-cause analysis with engineering.
• Mentor middle SDETs, review test designs, and set quality standards across the team.
• Partner with US-based development leads on shift-left practices, testability, and release readiness.

REQUIRED QUALIFICATIONS

• Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field.
• Programming: Strong proficiency in Python, including pytest, with deep understanding of OOP, software design principles, and test framework architecture.
• SQL & Data: Advanced SQL skills and strong understanding of relational and analytical data systems, including query execution internals.
• Data-intensive testing experience: Demonstrated experience testing data-intensive systems — query engines, ETL/ELT pipelines, streaming platforms, or analytical databases. Candidates with only web/UI QA backgrounds are not a fit.
• Testing experience: 5+ years in backend/system test automation, with demonstrated ownership of test strategy and infrastructure.
• CI/CD & DevOps: Solid experience architecting and maintaining Jenkins pipelines and test environments.
• Containers & Orchestration: Strong working knowledge of Docker and Kubernetes (running workloads, debugging pods, deploying complex environments).
• Cloud: Hands-on experience with at least one major cloud (GCP, AWS, or Azure); exposure to more than one is a strong plus.
• Version Control: Confident with Git / GitHub workflows and code review practices.
• English: Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team.
• Availability: Able to work EU hours with a 2–3 hour shift toward US West Coast time to ensure daily overlap with the client team.
• Leadership: Prior experience mentoring engineers, defining test strategy, or leading a QA/SDET function.

DESIRED SKILLS

• Deep experience testing REST APIs and backend microservices at scale.
• Hands-on with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines(e.g., Presto, Trino, or similar).
• Strong understanding of modern data lakehouse concepts, open table formats (Apache Iceberg), and data warehousing.
• Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight.
• Performance testing with JMeter or comparable load-testing tools at production scale.
• Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure.
• IaC tools such as Terraform.
• Deep understanding of query plan generation, query acceleration / materializations, and metadata integrity in distributed data systems.
• Prior experience leading a QA/SDET function in a data-platform or database engineering environment.
• Please note: We can consider only candidates currently residing in the EU, EEA, or the UK.

About Our Client:

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role:

We are looking for a Senior Software Engineer for the connectivity stack of a large-scale data platform. The work spans three areas:

• Client connectivity — drivers and client libraries used by applications and BI tools
• Source connectivity — connectors to databases and data systems, including authentication, metadata discovery, and query/data pushdown, with certification and upgrade support
• Agent & service connectivity — tool interfaces and integrations for AI-agent access to the platform

Deep expertise in one of these areas is enough — you'll grow into the adjacent ones over time. This is a role for an engineer who cares about API and protocol stability, backward compatibility, and interoperability with the tools enterprises actually use. You will lead the design and delivery of substantial components, working within an established architecture alongside US-based engineering reviewers.

This is a systems-level, backend engineering role focused on drivers, protocols, and distributed services — not application development or CRUD services.

Responsibilities:

• Lead the design and delivery of connectivity components — client drivers, source connectors, and service integrations — turning ambiguous initiatives into well-scoped, reviewable milestones
• Produce technical designs, explain architectural trade-offs, and surface compatibility, security, and delivery risks early
• Maintain backward compatibility and API/protocol stability; build compatibility, interoperability, and performance test suites
• Develop and maintain connectors for major BI tools, collaborating with the technology partners behind them
• Diagnose complex client/server, protocol, and distributed-system failures; drive root-cause analysis of customer-reported and escaped defects
• Improve diagnostics, logging, observability, and supportability of the connectivity stack
• Contribute upstream to open-source projects (e.g., Apache Arrow) where agreed
• Mentor engineers, participate in code and design reviews, and communicate progress and risks clearly across a distributed team.

Required Qualifications:

• B.S. or M.S. in Computer Science, Computer Engineering, or a related field — or equivalent practical experience
• 8+ years of production software engineering experience
• Deep proficiency in Java or C++, and the ability to work effectively in another systems/services language
• Experience designing and debugging APIs, protocols, client libraries, or distributed services
• Strong fundamentals: data structures, concurrency, asynchronous programming, networking, and failure handling
• A track record of comprehensive testing — unit, integration, compatibility, and performance
• Experience with production CI/CD, release processes, and engineering quality controls
• Working knowledge of SQL
• Comfortable with AI-assisted development workflows — using modern AI tools productively while critically validating their output
• Clear written and verbal communication in a distributed engineering environment; English Upper-Intermediate or higher (B2+)
• Availability to work EU business hours shifted 2–3 hours later for daily overlap with US West Coast mornings.

Desired Skills:

• JDBC, ODBC, ADBC, or database-driver development experience
• Apache Arrow (including Arrow Flight)
• SQL engines, databases, or data platforms
• Source-connector development for databases, warehouses, or SaaS systems
• MCP or agent-tool integrations
• OAuth, OIDC, TLS, and enterprise authentication flows
• Cross-platform native build, packaging, and release experience
• BI-tool interoperability (Power BI, Tableau) and partner collaboration
• Observability and production diagnostics
• Open-source contribution experience.

Details:

• Engagement: Long-term contract
• Location: Europe (EU / EEA / UK), remote
• Working hours: EU business hours, shifted 2–3 hours later for daily overlap with the US West Coast team

About Our Client:

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role:

We are looking for a Senior Software Engineer for the data catalog and enterprise data management layer of a large-scale lakehouse platform — the services that automate data ingestion and autonomously optimize Apache Iceberg tables. You will own features through the full development cycle, from design through deployment, in a multithreaded, distributed environment where scalability, performance, and always-on availability are the baseline expectations.

This is a systems-level, backend engineering role focused on data infrastructure internals — not application development or CRUD services.

Responsibilities:

• Own the full software development cycle — inception, design, development, testing, deployment — for catalog and data-management services
• Build and operate services for automated ingestion and autonomous optimization of Apache Iceberg tables
• Reason about concurrency and parallelization to deliver scalability and performance in multithreaded, distributed systems
• Drive performance tuning and system-efficiency improvements
• Work with Apache Foundation open-source projects, contributing upstream where agreed
• Participate in code and design reviews, upholding a high engineering bar
• Collaborate with product managers, support teams, and solution architects on feature requests and design updates
• Partner with US-based engineering leads on technical decisions.

Required Qualifications:

• B.S., M.S., or PhD in Computer Science or a related field
• 5+ years of software engineering experience, preferably focused on database systems or related fields
• Strong object-oriented programming skills in Java or C++
• Solid grounding in data structures and algorithms
• Hands-on experience with multithreaded and asynchronous programming patterns for scalable, performant systems
• A passion for engineering quality — zero-downtime upgrades, availability, resiliency, and uptime as first-class concerns
• Comfort with a fast-moving environment; strong ownership; the confidence to defend a technical position and the openness to be mentored
• Comfortable with AI-assisted development workflows — using modern AI tools productively while critically validating their output
• English Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team
• Availability to work EU business hours shifted 2–3 hours later for daily overlap with US West Coast mornings.

Desired Skills:

• Database internals and query planning
• Distributed systems: concurrency control, data replication, storage systems
• Apache Iceberg or other open table formats (Delta Lake, Hudi)
• Messaging systems: Kafka, NATS, or cloud pub/sub services
• Contributions to open-source data infrastructure (Apache projects especially valued).

Details:

• Engagement: Long-term contract
• Location: Europe (EU / EEA / UK), remote
• Working hours: EU business hours, shifted 2–3 hours later for daily overlap with the US West Coast team

About Our Client:

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role:

We are looking for a Senior Software Engineer to build and operate production AI agent and search services on top of a large-scale data platform. This is hands-on work at the intersection of distributed backend engineering and applied AI: multi-agent workflows, tool-execution infrastructure, retrieval and relevance, and integrations with multiple LLM providers — all running as real, customer-facing production services with the reliability expectations that implies.

Responsibilities:

• Design and implement scalable multi-agent workflows (including conversation state), tool-execution infrastructure, and data-aware tools working with catalogs, schemas, lineage, SQL, jobs, semantic metadata, data preparation, and visualizations
• Build search and retrieval capabilities with OpenSearch or equivalent — indexing, relevance tuning, hybrid keyword + vector search
• Integrate multiple LLM/model providers with secure configuration and graceful degradation
• Develop APIs and event contracts across REST, streaming/SSE, gRPC, protobuf, and SDKs, including UI integrations
• Operate, monitor, and improve production services — service health, logs, metrics, traces, search-cluster health, latency, and error rates; participate in the team's production-support model
• Investigate incidents, drive root-cause analysis, and ship durable fixes
• Design for permissions, tool approvals, multi-tenancy, and customer-data governance
• Maintain dependencies, apply security fixes, and reduce tech debt; produce designs, tests, runbooks, and documentation; lead technical discussions and review code.

Required Qualifications:

• B.S. or M.S. in Computer Science, Computer Engineering, or a related field — or equivalent practical experience
• 7+ years of relevant experience, or equivalent demonstrated senior-level impact
• Strong Java software engineering skills
• Strong grasp of concurrency, data structures, API design, testing, maintainability, and backward compatibility
• Solid background in distributed systems, microservices, cloud services, or data-intensive backends
• Hands-on experience with search technologies — OpenSearch, Elasticsearch, or Lucene — including vector search, embeddings, or relevance systems
• Experience building LLM applications, agent/tool workflows, RAG systems, or model-provider integrations
• Strong production instincts: diagnosing failures via logs, metrics, and traces; designing for fault tolerance, retries, cancellation, and recovery
• SQL and familiarity with data platform concepts: catalogs, metadata, schemas, governance, lineage
• Comfort leading ambiguous, cross-service work with clear stakeholder communication and strong written documentation
• Comfortable with AI-assisted development workflows — using modern AI tools productively while critically validating their output
• English Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team
• Availability to work EU business hours shifted 2–3 hours later for daily overlap with US West Coast mornings.

Desired Skills:

• LangChain4j or similar agent frameworks
• Python for AI services, evaluation harnesses, or sandboxed execution
• React and TypeScript
• gRPC, protobuf, Quarkus, Kubernetes, MongoDB, KV stores, event-driven architectures
• Apache Arrow, Apache Iceberg, OpenLineage, semantic layers, or data-governance systems
• AI quality evaluation: LLM-as-judge, model benchmarking, production AI metrics
• OpenSearch operations: index lifecycle management, relevance tuning, incident response
• Open-source contributions.

Details:

• Engagement: Long-term contract
• Location: Europe (EU / EEA / UK), remote
• Working hours: EU business hours, shifted 2–3 hours later for daily overlap with the US West Coast team

ABOUT OUR CLIENT

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

ABOUT THE ROLE

We are looking for a Senior Software Engineer for the connectivity stack of a large-scale data platform. The work spans three areas:

• Client connectivity — drivers and client libraries used by applications and BI tools
• Source connectivity — connectors to databases and data systems, including authentication, metadata discovery, and query/data pushdown, with certification and upgrade support
• Agent & service connectivity — tool interfaces and integrations for AI-agent access to the platform

Deep expertise in one of these areas is enough — you'll grow into the adjacent ones over time. This is a role for an engineer who cares about API and protocol stability, backward compatibility, and interoperability with the tools enterprises actually use. You will lead the design and delivery of substantial components, working within an established architecture alongside US-based engineering reviewers.

This is a systems-level, backend engineering role focused on drivers, protocols, and distributed services — not application development or CRUD services.

RESPONSIBILITIES

• Lead the design and delivery of connectivity components — client drivers, source connectors, and service integrations — turning ambiguous initiatives into well-scoped, reviewable milestones
• Produce technical designs, explain architectural trade-offs, and surface compatibility, security, and delivery risks early
• Maintain backward compatibility and API/protocol stability; build compatibility, interoperability, and performance test suites
• Develop and maintain connectors for major BI tools, collaborating with the technology partners behind them
• Diagnose complex client/server, protocol, and distributed-system failures; drive root-cause analysis of customer-reported and escaped defects
• Improve diagnostics, logging, observability, and supportability of the connectivity stack
• Contribute upstream to open-source projects (e.g., Apache Arrow) where agreed
• Mentor engineers, participate in code and design reviews, and communicate progress and risks clearly across a distributed team

REQUIRED QUALIFICATIONS

• B.S. or M.S. in Computer Science, Computer Engineering, or a related field — or equivalent practical experience
• 8+ years of production software engineering experience
• Deep proficiency in Java or C++, and the ability to work effectively in another systems/services language
• Experience designing and debugging APIs, protocols, client libraries, or distributed services
• Strong fundamentals: data structures, concurrency, asynchronous programming, networking, and failure handling
• A track record of comprehensive testing — unit, integration, compatibility, and performance
• Experience with production CI/CD, release processes, and engineering quality controls
• Working knowledge of SQL
• Comfortable with AI-assisted development workflows — using modern AI tools productively while critically validating their output
• Clear written and verbal communication in a distributed engineering environment; English Upper-Intermediate or higher (B2+)
• Availability to work EU business hours shifted 2–3 hours later for daily overlap with US West Coast mornings

DESIRED SKILLS

• JDBC, ODBC, ADBC, or database-driver development experience
• Apache Arrow (including Arrow Flight)
• SQL engines, databases, or data platforms
• Source-connector development for databases, warehouses, or SaaS systems
• MCP or agent-tool integrations
• OAuth, OIDC, TLS, and enterprise authentication flows
• Cross-platform native build, packaging, and release experience
• BI-tool interoperability (Power BI, Tableau) and partner collaboration
• Observability and production diagnostics
• Open-source contribution experience

DETAILS

• Engagement: Long-term contract
• Location: Europe (EU / EEA / UK), remote
• Working hours: EU business hours, shifted 2–3 hours later for daily overlap with the US West Coast team