Jobs Data Engineer

We are seeking a skilled ML/AI Engineer to join our team and deliver cutting-edge ML/AI models in the ASR domain and legal insights more broadly. The core of this role is building, deploying, and serving ML models in production. 

A key part of this role is speech engineering — prior ASR/speech experience is not a must, but a willingness to learn and grow into this domain is essential. Experience with LLM-based solutions and agentic flows is an advantage, not a requirement. 

What you’ll do: 

• Build, deploy, and serve ML models in production — the core of the role — optimizing inference performance, latency, and efficient GPU utilization. 
• Support and extend our speech solutions, including 3rd-party ASR integrations and self-hosted ML models. 
• Evaluate and optimize key ASR/ML metrics such as WER, latency, F1 score, EER, and DER. 
• Secondary: Integrate LLMs and agentic flows into production solutions where they add value, including fine-tuning existing models. 

What you’ll bring: 

Core (required): 

• Solid background in machine/deep learning, with 4+ years of experience. 
• Strong Python skills and experience working in Linux environments. 
• Familiarity with deep learning libraries (e.g., PyTorch, TensorFlow) and training workflows. 
• Experience with MLOps pipelines and serving/deploying models in production. 
• Experience optimizing models for inference, including GPU acceleration. 
• Experience with Docker, gRPC, and serverless / micro-services architectures on cloud infrastructure (AWS/GCP/Azure). 
• Experience with real-time / streaming systems and low-latency processing (e.g. streaming pipelines, live sessions). 

Nice to have (secondary / optional): 

• Experience building and productizing agentic flows and AI-driven solutions (1+ year). 
• Familiarity with LLM / agent orchestration frameworks such as CrewAI, AWS Bedrock, Temporal, AgentCore, or LiteLLM. 
• Prior ASR / speech experience — not required; willingness to learn this domain is what matters most. 

The Client is the UK’s leading fee-free mortgage broker. They are seeking experienced Data Engineer to join client’s data team. This role focuses heavily on core data engineering, architecture, and pipeline delivery within established frameworks rather than the presentation layer. The ideal candidate will be responsible for designing, building and optimizing scalable ingestion-to-consumption patterns and modern data warehousing principles.

Requirements

Must-Have Skills:

• Python / PySpark for Data Engineering: Strong experience writing PySpark notebooks in Fabric, building data transformation/cleansing logic, and notebook-based pipeline development.
• Medallion Architecture: Proven expertise in designing and implementing Bronze/Silver/Gold layered ingestion-to-consumption patterns, incremental loading, and transformation logic.
• Dimensional Modelling: Strong knowledge of Kimball-style fact/dimension design, SCD (Slowly Changing Dimension) handling, and Gold-layer conformance.
• T-SQL & DDL Proficiency: Expertise in warehouse schema design, writing stored procedures, and performance tuning.
• Pipeline Development & Orchestration: Practical experience with Dataflows Gen2, Fabric pipelines, notebook orchestration, scheduling, and dependency management.
• Good written and verbal English communication skills.

Nice-to-Have Skills:

• Governance & Security Implementation: Exposure to Microsoft Purview integration, Entra ID mapping, and workspace/access control architecture.
• Power BI & Semantic Modelling: Basic knowledge of DAX, semantic model design, and row/column/object-level security (RLS/CLS/OLS).

Job responsibilities

• Data Pipeline & Framework Development: Design, build, and orchestrate robust end-to-end data pipelines using Dataflows Gen2, PySpark notebooks and native orchestration tools.
• Architecture & Storage Layer Management: Implement and maintain Medallion Architecture (Bronze, Silver, Gold layers), ensuring proper incremental loading strategies and layer-specific transformation logic.
• Data Warehousing & Dimensional Modelling: Build Kimball-style fact and dimension models, manage Slowly Changing Dimensions (SCDs), and ensure Gold-layer data conformance for analytics consumption.
• Data Transformation & Optimization: Write clean, modular Python/PySpark code and T-SQL/DDL logic for data cleansing, schema design, stored procedures, and query performance tuning.

Summary

Expert Data Engineer with 3+ years in Power BI Pro, Azure SQL, and complex ETL pipeline development. Skilled in DAX, Power Query, and Azure Synapse notebooks for advanced data analytics and performance tuning. Proven expertise in optimizing Azure Data Lake Storage with Parquet file techniques and managing large-scale backend data processing. Experienced in Agile methodologies, data warehousing, and software engineering best practices, delivering high-quality solutions in cross-functional teams.

Role Overview:
 

The Senior/Expert Data Engineer position is a contract, long-term engagement based in Ukraine, focused on delivering advanced data engineering solutions using Databricks, Power BI, and SQL. The role is embedded within a global consulting and auditing firm supported by a custom product engineering company. The candidate will join a cross-functional development team responsible for engineering innovative data experiences and solving complex business challenges for multinational organizations and scaling startups.

Key Responsibilities:

• Design, develop, and deploy Power BI solutions, including dashboards and reports that provide critical business insights.
• Create and implement robust data models optimized for performance and efficient query execution.
• Optimize Power BI reports and dashboards by improving query speed and data model efficiency.
• Contribute to the design, coding, configuration, and management of data ingestion processes, supporting both near real-time and batch ETL pipelines across multiple data storage systems.
• Perform performance tuning and optimization of complex SQL and DAX queries to enhance data processing efficiency.
• Develop, execute, and maintain data processing workflows using Azure Synapse notebooks.
• Manage and optimize data storage solutions within Azure Data Lake Storage (ADLS), focusing on Parquet file optimization techniques such as partitioning and compression.
• Identify platform gaps and implement improvements to enhance quality, robustness, maintainability, and speed.
• Cross-train team members on emerging technologies and continuously learn from peers to foster knowledge sharing.
• Contribute actively to the unit’s community-building activities, participate in conferences, and uphold best practices and excellence in engineering.

Projects:

The job description does not specify individual project names or dates. However, the candidate’s contributions span multiple projects involving the following contexts and responsibilities:

• Power BI Solution Development: Serving as the lead data engineer responsible for designing and deploying Power BI dashboards and reports, performing advanced data analytics, and implementing complex DAX calculations and Power Query transformations to support business decision-making.
• ETL Pipeline Engineering: Managing and optimizing complex ETL pipelines involving data ingestion, batch processing, and near real-time data flows across diverse data storages, utilizing Azure Data Factory and Azure Synapse Analytics.
• Data Storage Optimization: Overseeing data storage management in Azure Data Lake Storage, applying advanced Parquet file optimization techniques such as partitioning and compression to improve data retrieval and storage efficiency.
• SQL and DAX Performance Tuning: Leading efforts to optimize complicated SQL queries and DAX formulas to enhance report and dashboard performance.
• Azure Synapse Notebook Development: Developing and maintaining data processing workflows within Azure Synapse notebooks to support large-scale backend data processing and analysis systems.

Technologies, Tools, and Methodologies Used:

• Databricks
• Power BI Pro (Desktop and Service)
• DAX (Data Analysis Expressions)
• Power Query
• SQL (Azure SQL Database, Microsoft SQL Server)
• Azure Data Lake Storage (ADLS)
• Parquet file format with optimization techniques (partitioning, compression)
• Azure Synapse Analytics and Notebooks
• Azure Data Factory
• ETL and data integration processes
• Agile software development methodologies, including SCRUM

• Software engineering best practices: coding standards, code reviews, source control, build processes, testing, and operations

   

Additional Contributions and Skills:

• Strong problem-solving and analytical skills with meticulous attention to detail.
• Excellent communication skills, capable of presenting complex data clearly and concisely to stakeholders at various organizational levels.
• Experience collaborating within cross-functional teams and contributing to community-building and knowledge sharing.
• Demonstrated ability to learn new technologies quickly and independently.
• Proven track record of delivering high-quality software on large, complex, cross-functional projects.

Main requirements

Snowflake Experience

The person should be proactive, well-organized, and an effective communicator, able to independently drive tasks forward, keep processes under control, and communicate clearly with the team and stakeholders.

Requirements

Senior Data Enginer

Snowflake — core development

• Writing and maintaining production views, secured views and stored logic in Snowflake
• Understanding of role-based access control: users, roles, GRANTs, warehouse and database entitlement models
• Enough query-tuning instinct to build views over large fact tables without wrecking performance — partition pruning, clustering awareness, avoiding SELECT *

Microsoft SQL Server

• T-SQL development
• Migrating legacy tables, views and stored procedures to Snowflake

Previous ETL Tooling Experience

Bonus Points

BI and semantic layer

• Sigma Computing — connection setup, workbooks, embedding, AI/Cortex configuration. We are rolling Sigma out now and retiring Tableau Desktop.
• Tableau — data source management, extract vs live strategy, extract scheduling and dependency mapping

Documentation and code review

• Producing data-flow and architecture diagrams
• Reviewing SQL/pipeline code to a standard — we have a code review backlog in other areas because there aren’t enough qualified SQL reviewers. A contractor who can act as a second reviewer is disproportionately valuable.

Azure DevOps (aka ADF Pipelines sync’d with Github)

• CI/CD pipelines for database and ADF artefacts, service principal / client secret configuration, release troubleshooting

External API ingestion

• Consuming and loading third-party APIs into the warehouse (e.g. FX/exchange rate feeds), including auth and error handling
• Snowflake Git integration — connecting a Git repository to Snowflake, versioning database objects and deploying from a branch, plus general source-control discipline for SQL and pipeline code
• Snowflake Streamlit — building lightweight in-warehouse data apps as an alternative to a full BI workbook where the audience is small or the use case is operational
• Python for data engineering and Snowpark
• Snowflake Cortex / LLM-in-warehouse features
• dbt or equivalent transformation tooling (not in use today, but relevant if we modernise)

Working attributes we need

• Comfortable being the second pair of hands on a one-person team — takes a ticket end-to-end without daily direction
• Documents as they go; we are explicitly trying to reduce single-person key-man risk
• Cost-aware: several of our decisions are spend-driven, not purely technical

English - Andvanced

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

We are looking for an experienced Senior Data Engineer to join a growing Data Engineering and Analytics department. In this role, you will design and develop advanced data solutions for complex customer environments, with a strong focus on Google Cloud Platform and modern GCP data technologies. You will work across the full data lifecycle- from architecture and data modeling to pipeline development, data platforms, analytics, and production deployment.

Key Responsibilities:

• Design and develop scalable data solutions on GCP.
• Lead the technical design and implementation of customer data projects.
• Understand business and technical requirements and translate them into effective data architectures.
• Build and maintain ETL/ELT pipelines, Data Lakes, Lakehouses, and cloud-based Data Warehouses.
• Design data models and integration processes for Batch and real-time workloads.
• Work with structured, semi-structured, and unstructured data.
• Select the appropriate technologies based on performance, scalability, security, and cost requirements.
• Implement data quality, monitoring, governance, and orchestration processes.
• Work closely with Data Architects, Data Engineers, DevOps teams, analysts, and customer stakeholders.
• Participate in the development of analytics, AI, and ML solutions where relevant.
  
  Requirements:
• At least 5 years of professional experience as a Data Engineer – mandatory.
• Proven hands-on experience developing data solutions on GCP – mandatory.
• Experience with data visualization tools such as Looker, Power BI, Tableau, or QuickSight.
• Experience with data modeling, orchestration, performance optimization, and large-scale data processing.
• Strong Python development skills, including building data pipelines and ETL/ELT processes.
• High proficiency in SQL – mandatory.
• Experience designing and developing cloud-based Data Warehouses and Lakehouse solutions.
• Experience with ETL/ELT and transformation tools such as dbt, Dataform, Rivery, or similar platforms.
• Familiarity with CI/CD, Git, Infrastructure as Code, and production deployment practices.
• Strong analytical and problem-solving skills with excellent attention to detail.
• Ability to learn new technologies independently and work across multiple projects.
• Strong experience with several of the following GCP services: BigQuery, Cloud Storage, Dataflow, Dataproc, Cloud Composer, Cloud Run or Cloud Functions
• Fluent English.
  
  Advantages
• Hands-on experience with AWS or Microsoft Azure data services.
• Experience with services such as AWS Glue, Redshift, EMR, Kinesis, Azure Data Factory, Synapse, or Databricks.
• Experience with real-time data processing and streaming architectures.
• Experience with Kafka or other event-driven platforms.
• Knowledge of AI and ML services such as Vertex AI, Gemini, BigQuery ML, SageMaker, Bedrock, or Azure Machine Learning.
• Relevant GCP professional certifications.
• Previous experience working in consulting or customer-facing technology projects.

Шукаємо у команду Senior DevOps / SRE Engineer (Remote).

Якщо ви маєте бажання працювати в невеликому колективі разом із сильною командою, радо розглянемо ваш відгук! Ми шукаємо не лише сильного DevOps Engineer, а й інженера із досвідом Site Reliability Engineering (SRE), який готовий брати на себе технічне лідерство, ділитися знаннями та допомагати розвиватися іншим членам команди. Націлені на довгострокову співпрацю з компенсацією, що базуватиметься на вашому досвіді роботи.
 

Завантаженість: повна зайнятість — 40 год/тиждень. Робота віддалена. Оплата погодинна.
 

Стек технологій:

- Scripting: Bash | Python | Makefile

- Containers and Orchestration: Kubernetes | Docker | GKE

- Infrastructure as Code (IaC): Terraform | Ansible

- CI/CD & Automation: GitHub Actions | CircleCI | TravisCI

- Cloud Providers & IaaS: AWS | GCP | Azure | Hetzner

- Databases: SQL | NoSQL (PostgreSQL, Redis…)

- Authorization and Security: OpenSSL

- Observability and Monitoring: Prometheus | Grafana | ELK Stack (Elasticsearch, Logstash, Kibana)

- Operating Systems: Linux
 

Site Reliability Engineering (SRE):
- SLI / SLO / SLA | Incident Response | Root Cause Analysis (RCA) | - High Availability | Capacity Planning | Disaster Recovery | 
- Performance Optimization | Reliability Engineering | 
 

Буде плюсом:

- Infrastructure Management: Developing and implementing infrastructure, configuration, and code branching strategies.

- Quality Assurance & Testing: Conducting integration, regression, UI/UX, API, load/stress, and other types of testing.

- Bug Tracking & Issue Management: Identifying, documenting, and tracking software defects and bugs.

- Performance & Optimization: Monitoring and analyzing quality metrics to identify areas for improvement.

- Automated Testing: Experience with automated testing frameworks such as Selenium, Appium, JMeter, etc.

Mentoring & Leadership:
- Досвід менторингу Junior/Middle інженерів, проведення code review, технічних обговорень, knowledge sharing та допомоги команді у професійному розвитку.
 

Вимоги до кандидата:

- Досвід роботи DevOps Engineer та практичний досвід Site Reliability Engineering (SRE)
- Досвід побудови та підтримки високодоступних production-систем із високими вимогами до reliability.

- Досвід роботи з Kubernetes у production-середовищі

- Розуміння принципів високої доступності, масштабування та відмовостійкості систем

- Досвід побудови та підтримки CI/CD процесів

- Англійська мова — Intermediate+

- Уміння слідувати code conventions

- Здатність навчатися

- Здатність наполегливо працювати

- Критичне мислення

- Витривалість

- Спроможність лаконічно та чітко пояснювати свою думку

- Бажання ділитися знаннями, проводити менторинг та допомагати розвиватися іншим членам команди

- Відданість нашим проєктам

- Прозорість
 

Що отримаєте:

- Віддалені умови роботи

- Удосконалення навичок планування та продуктивності

- Робота у вимогливому, але дружньому середовищі серед A-гравців

- Регулярний зворотний зв'язок і допомога в плануванні вашого навчального процесу та кар'єрного зростання

- Незалежність від місцевого ринку та долучення до глобальної економіки

- Підвищення рівня володіння англійською мовою

- Корпоративні навчання, технічні воркшопи та тренінги для постійного підвищення кваліфікації

We are looking for a highly skilled Backend Engineer to help design and scale the core services powering our platform. 

You will work on business-critical backend services, contribute to architectural decisions, and help solve complex scalability, performance, and reliability challenges. 

What you'll do:

• Design backend services capable of handling growing traffic and increasing product complexity
• Build APIs and internal platform components that become the foundation for future development
• Improve system reliability, observability, and operational efficiency
• Analyze bottlenecks and optimize performance across services and databases
• Solve production issues and prevent them from recurring through better architecture and engineering practices
• Drive technical discussions and influence long-term engineering decisions
• Partner with product and engineering stakeholders to deliver solutions that balance speed and quality

You are likely a strong fit if:

• You have spent years building and operating backend systems in production
• Node.js and TypeScript are technologies you know deeply rather than tools you've only used occasionally
• You understand trade-offs in system design and can justify architectural decisions
• You are comfortable owning services end-to-end, from implementation to monitoring and incident response
• You have practical experience with AWS and modern cloud-native development
• You have worked with document databases, caching layers, and asynchronous processing patterns
• You can quickly isolate problems in complex systems and drive them to resolution

Preferred Qualifications

• Degree in Computer Science, Mathematics, Software Engineering, or a related technical field
• Background in competitive programming, algorithmic competitions, or programming olympiads
• Experience with event-driven architectures and asynchronous processing
• Hands-on knowledge of messaging systems and distributed workflows
• Experience building systems in fintech, trading, marketplaces, or other high-load environments
• Experience working in startup or scale-up companies
• Strong understanding of system design, algorithms, and data structures

Preferred Qualifications:

• Degree in Computer Science, Mathematics, Software Engineering, or a related technical field

On behalf of our Client, Scalors is looking for a DevOps Engineer to join a remote team for a full-time position.
 

About Client:
Our Client delivers cutting-edge software solutions for the cruise and hospitality industries, driving efficiency and reliability across mission-critical systems. Our Infrastructure & Edge Operations team ensures that our global platforms run smoothly, securely, and at scale.

Role summary:

• Remote first, work from anywhere, with occasional travel to customer sites or ships as required for onboarding or incident response. Candidate must be available for on call rotations.
• You will own build, release, operations, observability and deployment automation for cloud and shipboard environments.
• You will design and operate secure, resilient networks and runtime platforms that support microservices, event streaming and offline sync for guest facing systems such as POS, gangway, dining and guest services.
• You will be customer facing, and able to translate shipboard constraints into reliable deployment and support practices.
• You will also use AI tools and techniques to design, automate and improve our infrastructure, observability and incident operations.

Core responsibilities:

• CI CD and release automation, design and maintain CI CD pipelines for multi environment deployments, including cloud, shipboard on premise and air gapped scenarios.
• Infrastructure as code, author and maintain Terraform, Ansible or Pulumi templates for cloud and on premise platforms.
• Kubernetes and container platforms, operate and tune Kubernetes clusters in cloud and shipboard edge nodes, manage Helm charts or Kustomize manifests and GitOps flows.
• Shipboard network design and troubleshooting, configure IP networks, VLANs, routing, NAT, port forwarding, DNS, NTP and firewall rules for shipboard deployments, including satellite link and VSAT awareness.
• Edge constraints and offline design, design resilient services for intermittent connectivity, offline first clients, local stores such as SQLite or Couchbase Lite, CRDT or other reconciliation strategies.
• Black box microservice handling, integrate and operate against third party or opaque services using robust contract testing, timeouts and circuit breaker patterns, and observability wrappers to detect failures without requiring changes to the black box.
• Observability and diagnostics, deploy and operate Prometheus, Grafana, OpenTelemetry, Jaeger, Elastic or OpenSearch, Loki and tracing to achieve end to end visibility across cloud and shipboard.
• Messaging and data platforms, operate Kafka and topic management, ensure broker resiliency and correct retention and consumer behavior for shipboard replication scenarios.
• Security and compliance, implement mTLS, certificate lifecycle, Vault secrets management, vulnerability scanning, container image signing, and operate according to PCI and GDPR requirements on payment and guest data flows.
• Hardening and incident response, lead troubleshooting for production incidents, runbooks, on call rotations, post incident reviews and automated rollback strategies.
• Automation and developer enablement, provide tools and templates that enable developers to produce production quality artifacts, and self service infrastructure for test and demo environments.
• Customer engagement, collaborate with customer IT to validate IP designs, test failover scenarios and document network and deployment runbooks.
• Backups and disaster recovery, implement backup and restore for stateful components, test DR in constrained network conditions.
• Cost and capacity planning, monitor capacity, plan cluster sizing and network bandwidth usage, and recommend changes to reduce cost and risk.
• AI driven design and operations, apply AI and machine learning tools to improve infrastructure design, incident management, observability and automation, while maintaining strict security and audit controls.

Required skills and experience:

• 3 plus years operating production cloud and container platforms, or equivalent experience.
• Strong practical knowledge of Kubernetes, Docker and container runtimes.
• Hands on experience with Terraform or other IaC tools, and configuration management such as Ansible.
• Deep understanding of IP networking concepts, VLANs, routing, NAT, DNS, DHCP, bonding and firewall policies, with experience applying these on site in constrained WAN environments.
• Experience operating Kafka, MySQL, Elasticsearch or OpenSearch, Redis or Hazelcast, and understanding replication and retention trade offs.
• Observability and tracing experience, with Prometheus, Grafana, OpenTelemetry or Jaeger, and log pipelines in Elastic or OpenSearch or Loki.
• Strong scripting and automation skills in shell, Python or Go.
• Solid security fundamentals, including TLS, PKI, secrets management, container image security and familiarity with PCI compliance basics.
• Excellent troubleshooting skills, including working in constrained network conditions, and customer facing communication skills.
• Experience with Git based workflows, and at least one CI CD platform such as Jenkins, GitLab CI, ArgoCD or GitHub Actions.
• Practical experience using AI tools and models in production workflows for infrastructure as code, observability summarization and automated runbook generation, including knowledge of model governance, data redaction and secure private deployments.

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: 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 the role

We're looking for a middle DevOps / SysOps engineer to take care of the infrastructure our product runs on: on-prem virtualization, network and VPN connectivity between sites, and the delivery pipelines on top of it. The team is small, so you get real ownership from the start — and room to grow into your own areas of responsibility.

Responsibilities

* Operate and develop on-prem virtualization: VMware ESXi + vCenter (clusters, resource pools, storage, patching and version upgrades)

* Administer network infrastructure: MikroTik, Cisco, pfSense — VLANs, routing, NAT, firewall policies

* Build and maintain WireGuard site-to-site and client VPN topologies between offices, labs and cloud

* Maintain Ubuntu servers: systemd, journald, configuration management, hardening, monitoring and alerting

* Support Docker-based build and deployment workflows

* Develop and maintain CI/CD pipelines in GitHub Actions

* Manage S3-compatible object storage for backups and build artifacts

* Own backup and restore procedures, including regular recovery testing

* Write technical documentation and runbooks for what you build

* Participate in incident response and on-call rotation

Requirements

* 2+ years of commercial experience in DevOps / system administration / infrastructure

* Production experience with VMware ESXi and vCenter

* Hands-on experience with at least two of: MikroTik RouterOS, Cisco, pfSense / OPNsense

* Networking fundamentals: L2/L3, VLAN, static and dynamic routing, NAT, firewall policies, DNS, DHCP, TLS, SSH

* WireGuard (or IPsec / OpenVPN): configuring tunnels and routing between sites, troubleshooting asymmetric routing

* Docker and Docker Compose: builds, registries, networking, volumes

* CI/CD with GitHub Actions (or GitLab CI with readiness to move to GHA)

* Linux (Ubuntu): confident CLI, systemd, journald, bash scripting

* Basic experience with S3-compatible storage or a public cloud provider (AWS / Azure / GCP / Hetzner)

* Monitoring and logging basics: Zabbix, Prometheus + Grafana, or ELK

* English for technical communication (reading docs, written async communication)

Nice to have

* Cisco FTD / FMC, Cisco ISE (802.1X, NAC, posture)

* Certifications: VCP-DCV, CCNA / CCNP Security, MTCNA / MTCRE / MTCINE, LFCS / RHCSA, AWS SAA

* Other VMware products: vSAN, NSX, Horizon (VDI), VCF, Site Recovery Manager, Veeam Backup & Replication

* Automation and IaC: Ansible, Terraform, Python

* Information security fundamentals: PKI, secrets management, hardening baselines (CIS), secure boot

* Bare-metal / Raspberry Pi / embedded Linux

* Experience with isolated or air-gapped environments

What we offer

* Competitive salary

* Reservation from mobilization

* Office in Kyiv with shelter access, generator and Starlink

* Possibility of hybrid work format

* Impact on improving our country's defense capabilities

* 21 days of vacation + public holidays, sick leaves

We are looking for a highly skilled Senior Data Platform Engineer to join our Data Platform team and play a key role in designing, building, and evolving the company’s data infrastructure.

This is a hands-on engineering position focused on developing scalable data platforms, high-volume ingestion pipelines, and the foundational data systems that power analytics, product applications, AI workloads, and large-scale model execution. You will help architect our data lake, build reliable ingestion capabilities at scale, and shape the core infrastructure that supports the company’s future growth.

This is an exciting opportunity to work with cutting-edge technologies and have a defining impact on the architecture and evolution of our data platform.

Requirements:

• 5+ years of experience as a Data Platform/Infra Engineer
• Proven track record of building and operating scalable data infrastructure specifically within Data Lake architectures.
• Proven experience designing and operating large-scale data processing workloads on Kubernetes, including workload autoscaling with KEDA.
• Strong proficiency in Python and SQL.
• Hands-on experience with Infrastructure as Code, preferably Terraform.
• Experience with managing a data orchestration platform such as Airflow or Prefect
• Experience with Snowflake.

Responsibilities:

• Build complex, high-volume batch and near-real-time ingestion services while helping evolve the platform’s streaming capabilities.
• Design and implement data solutions for all application requirements in a distributed microservices environment
• Develop and optimize large-scale data pipelines for batch and streaming use cases.
• Ensure data quality, compliance, and governance.
• Manage and optimize Kubernetes infrastructure, utilizing KEDA to dynamically scale resources for large-scale data processing workloads.
• Own the full lifecycle of our data stack using Terraform and Kubernetes, from provisioning to application-level frameworks.
• Provide technical guidance for the team, drive best practices around infrastructure, CI/CD, testing, and system design.
• Deep-dive into memory management and performance tuning to ensure our large-scale distributed systems are both cost-effective and lightning-fast.

What we offer:

• Comfortable environment, challenging tasks and a long-term interesting project;
• Mobilization reservation available upon successful completion of the probation period (for Ukrainian colleagues).
• Covered 20 days of vacation;
• Working with top notch equipment;
• Bookkeeping by a professional accountant;
• Help and support from our caring HR-team;

We are looking for a Senior DevOps Engineer to build and evolve the infrastructure behind Kyivstar's Big Data products. You will own the full lifecycle of our cloud and on-premises environments - from architecture and provisioning to CI/CD, observability and incident response 

Requirements

- 3+ years of experience as a DevOps Engineer.

- Practical experience with cloud providers (AWS preferred).

- Experience building CI/CD pipelines (preferably GitLab).

- Strong hands-on experience with Docker and Kubernetes.

- Practical experience with Infrastructure as Code (IaC) (preferably Terraform).

- Solid understanding of Unix/Linux operating systems and networking fundamentals.

- Strong hands-on experience with scripting languages (Bash and/or Python).

- Experience with relational and non-relational databases (e.g., PostgreSQL or similar).

- Experience with monitoring and alerting tools (e.g., Prometheus, Grafana).

- Proven experience working with remote/distributed teams.

- Experience with AI agents or AI-driven tooling is a plus.

Responsibilities

- Implement solutions for Big Data and AI products.

- Design and implement CI/CD pipelines tailored for Big Data solutions.

- Manage and maintain AWS and on-premises infrastructure.

- Monitor, troubleshoot, and continuously improve system observability.

- Automate software deployment, monitoring, and routine operational tasks.

- Support staging/production environments, manage release cycles, and assist customers.

We offer

•            A unique opportunity to shape the future of Big Data products at Ukraine's leading telecom operator

•            Work on high-impact initiatives that create value across multiple business functions

•            Collaboration with experienced business, data and technology professionals

•            Remote work with the possibility to visit the office

•            Competitive salary and annual bonus

•            Paid vacation and sick leave

•            Flexible working hours

•            Medical and life insurance

•            Professional development and career growth opportunities

•            A friendly, collaborative and innovation-driven working environment