Jobs Data Engineer

We are looking for a Senior Data Engineer to design and build scalable data platforms that process large volumes of data for analytics, reporting, and business-critical applications.

You will work with distributed data processing systems, cloud infrastructure, streaming platforms, and modern data pipelines. We are looking for an engineer who can independently own production solutions and solve complex performance and architecture challenges.

Mandatory Skills

Programming & Data Processing

• Strong Python development skills
• Advanced SQL (complex queries, optimization, execution plans)
• Strong commercial experience with Apache Spark / PySpark
• Experience optimizing Spark jobs (partitioning, shuffle, joins, skew handling)

Data Engineering

• Experience building production-grade ETL / ELT pipelines
• Strong experience with Apache Airflow
• Strong hands-on experience with Apache Kafka
• Understanding of batch and streaming data processing architectures

Infrastructure & Storage

• Experience with relational databases (PostgreSQL, MySQL or similar)
• Data modeling and query optimization
• Hands-on experience with at least one cloud platform (AWS, Azure or GCP)
• Experience working with Docker, Linux, Git, and basic CI/CD pipelines

Desired Skills

• Databricks, Snowflake or similar cloud data platforms
• Kubernetes
• CDC pipelines (Debezium or similar)
• Modern analytical/storage systems (ClickHouse, Trino, Iceberg, Delta Lake)
• Monitoring tools (Grafana, Prometheus)

Responsibilities

• Build scalable batch and streaming data pipelines
• Develop and optimize Spark/PySpark data processing jobs
• Build Kafka-based ingestion and event-driven pipelines
• Design and maintain Airflow orchestration workflows
• Optimize SQL queries and improve pipeline performance
• Investigate production issues and improve system reliability
• Participate in architecture and technical design discussions

Senior-Level Expectations

• Independently design scalable data pipelines
• Debug and optimize distributed production systems
• Solve performance bottlenecks in Spark and SQL workloads
• Make technical decisions with minimal supervision
• Take ownership of production solutions end-to-end

Soft Skills

• Strong problem-solving skills
• Ownership and accountability
• Ability to work independently
• Good communication and collaboration skills
• Proactive engineering mindset

Summary

# Job Title

Product-Minded Full-Stack / AI Engineer for Web Data Intelligence Platform

# Job Description

We are building an AI-powered platform that collects, structures, and analyzes information from public websites and documents.

The system needs to process messy real-world data from many organizations, extract useful structured information, store it in a database, and present it through a user-facing dashboard.

This is not a basic scraping project. We are looking for someone who can think through system architecture, data pipelines, database structure, AI extraction workflows, and product design.

The right person should be able to take an existing MVP, understand the logic behind it, and help redesign it into a more scalable and configurable system.

# What You’ll Work On

You will help design and build a platform that can:

* Discover and process public web pages and documents.
* Extract structured information from unstructured text and PDFs.
* Normalize information into a database.
* Track updates over time.
* Detect duplicates and changes.
* Classify and score records based on configurable rules.
* Match structured records to user-defined profiles.
* Support a dashboard for review, filtering, and workflow management.
* Make the system configurable across different use cases.

# Required Skills

Strong fit if you have experience with:

* Python and/or Node.js
* Web crawling / scraping
* PDF and document extraction
* LLM-based extraction and classification
* Database design
* Full-stack development
* Data pipelines
* AI workflow design
* Prompt engineering
* Handling messy real-world data

Bonus if you have worked with:

* Public web data
* Search or monitoring systems
* Workflow dashboards
* Vector databases
* Supabase / Postgres
* Playwright
* OpenAI / Claude APIs
* LangChain / LlamaIndex or similar tools

# Important

We are not looking for someone who only knows how to scrape websites.

We are looking for someone who can help turn an MVP into a structured, scalable intelligence platform.

You should be comfortable thinking about:

* Data models
* Extraction quality
* Source reliability
* Change detection
* Deduplication
* Configurable scoring logic
* Human review workflows
* Product usability

# What We Are Looking For

A strong candidate will think in terms of:

* Sources
* Documents
* Records
* Evidence
* Configurations
* Profiles
* Matches
* Processing runs
* Review workflows
* Data quality
* Deduplication
* Change tracking
* Explainable scoring

A weak candidate will only talk about scraping pages.

# Engagement

This will start as a short test project. If successful, it can become an ongoing engineering role.

We are looking for someone who can eventually take ownership of the platform architecture and development.

# To Apply

Please answer the following questions:

1. Describe a similar system you have built or would know how to build.
2. How would you separate use-case-specific logic from the core platform?
3. How would you detect whether a record is new, updated, duplicate, stale, or no longer relevant?
4. What database schema would you start with?
5. What would you automate, and where would you keep human review?
6. Please share examples of relevant work if available.

Applications without thoughtful answers will not be considered.

Job Description
Extensive software development experience, including experience working on complex backend or data infrastructure projects.
Strong hands-on experience with Apache Iceberg .

Experience with Scala.

Hands-on experience developing backend services, data-processing engines, infrastructure components.
Programming experience in C /or C++ is highly desirable / preferred, the role is primarily focused on backend/system-level engineering rather than full-stack application development.
Deep understanding of distributed systems, data processing, storage engines, or data infrastructure.

Strong knowledge of data consistency, transactions, schema evolution, partitioning, compaction, and performance optimization.

Proven ability to troubleshoot complex production and customer issues.

Strong ownership mindset and the ability to operate effectively in areas with limited documentation or historical knowledge.

Excellent communication and collaboration skills.

Preferred Qualifications: 
Big Data Frameworks: Hands-on experience with distributed data-processing technologies such as Apache Spark, Flink, Trino, or Presto.
Cloud Object Storage: Experience working with cloud storage platforms, including Amazon S3, Google Cloud Storage (GCS), or Azure Data Lake Storage (ADLS).
Legacy Modernization: Proven track record of modernizing or gradually improving a mature codebase without disrupting existing customers.
Job Responsibilities
Architect & Build: Lead the architecture, design, and implementation of highly scalable, complex backend systems and robust data infrastructure using Iceberg.
Data Lake Engineering: Design and manage enterprise-grade data lake solutions leveraging Apache Iceberg or equivalent table formats, ensuring optimal data consistency, transactions, schema evolution, partitioning, and compaction.
Performance Optimization: Maximize system throughput, minimize latency, and optimize resource utilization across large-scale distributed data processing systems.
Production Excellence: Systematically diagnose, troubleshoot, and resolve complex, high-impact production and customer-facing infrastructure issues.
Codebase Modernization: Champion the gradual improvement and modernization of a mature, production-critical codebase without causing disruption to active customers or services.
Technical Leadership & Collaboration: Act as a technical authority, fostering strong communication and collaboration across engineering teams to align on technical objectives.
Navigate Ambiguity: Exercise a strong ownership mindset to operate effectively and deliver high-quality outcomes in areas with limited documentation or historical knowledge.
Department/Project Description
We are seeking an expert Iceberg Engineer to design, optimize, and scale our next-generation multi-cloud data lakehouse architecture across AWS and Azure. The ideal candidate is a backend/system engineer with strong experience building engines, infrastructure, or high-performance backend components. In this role, you will leverage client's Open Lakehouse (integrated with Client's Talend Cloud) to establish a low-overhead, high-throughput data foundation. You will manage automated data ingestion, implement continuous table optimization, handle cross-cloud data mirroring, and ensure seamless multi-engine access without vendor lock-in.
 

Our client is a performance rights organization in the United States. It collects blanket license fees from businesses that use music, entitling those businesses to play or sync any songs from the client’s repertoire of over 22.4 million musical works. On a regular basis, the client distributes the money to songwriters, composers, and music publishers as royalties to those members whose works have been performed.

Requirements:

• Databricks Expertise: Minimum of 3+ years of proven, previous Databricks administration experience in a complex, multi-tenant enterprise environment.
• Advanced Terraform: Strong Terraform skills. You must have hands-on experience building and maintaining reusable modules specifically utilizing the Databricks Terraform Provider.
• Strong understanding of cloud-native IaC (Infrastructure as Code) like Terraform for automating instance provisioning
• Cloud IAM Mastery: Deep, practical knowledge of Cloud Identity and Access Management (IAM), including writing secure IAM policies, managing roles, cross-account access, and secrets management.
• Robust cloud networking experience
• Scripting: Proficiency in Bash

Job responsibilities:

• Environment Ownership: Own the technical implementation of all Databricks environment configuration changes across multi-workspace environments.
• Platform Lifecycle: Manage Databricks runtimes, cluster policies, and coordinate seamless platform upgrades.
• Infrastructure as Code (IaC): Utilize strong Terraform skills to programmatically provision, update, and manage all Databricks resources (workspaces, clusters, tokens, policies) and cloud infrastructure, eliminating manual configurations.
• Cloud Security & Identity (IAM): Architect and enforce secure access models. Manage Cloud Identity and Access Management (IAM) integrations for users, groups, and service principals.
• Secure Cloud Networking: Design, implement, and maintain secure cloud networking architectures for Databricks.
• Cost Optimization: Actively review current environment setups—including cluster configurations, instance types, and data storage parameters—to identify and execute cost-optimization opportunities.
• Efficiency Strategies: Provide expert input on automation, auto-scaling, and monitoring strategies to drastically reduce ongoing compute and storage costs.

📍 Location: EU-based, Remote
💼 Cooperation type: Full-time

We’re looking for a skilled Data Engineer to join our Analytics team. 

We are building the data platform that serves both our analytics and operational data needs. In this role you will own significant parts of the platform architecture — from design through deployment — and build the pipelines and services that make the company’s data flow reliably between systems. You will work with large, complex datasets and high-throughput pipelines, and you will own a major greenfield project connecting our production systems with our CRM.

About us:
Stape is a global product-driven IT company and the #1 leader in the server-side tracking market. We’re building a powerful, technically complex product that simplifies server-side tracking for marketers and website owners. Our platform processes over 5 billion requests daily, helping improve tracking accuracy and data privacy for more than 200, 000 clients worldwide. We work closely with top tech partners, including Meta, LinkedIn, Google, Snapchat, and TikTok to provide advanced tracking capabilities.


Skills and experience
 

• Minimum 4 years of experience as a data engineer (platform/pipeline building, not only report maintenance).
• At least an upper-intermediate level of English (written and spoken).
• Bachelor’s degree in Computer Science, Engineering, or another related technical field.
• Extensive knowledge of SQL and Python.
• Experience organizing, monitoring, and maintaining data infrastructure: managing ETL/ELT processes, writing tests for data pipelines, and monitoring data consistency.
• Practical experience with GCP: BigQuery, Cloud Logging, Cloud Storage, Cloud Functions, Cloud Run, Datastream, Pub/Sub.
• Practical experience with Dataform (or dbt).
• Experience with a workflow orchestrator (Apache Airflow or similar) — scheduling, dependency management (DAGs), retries, and backfills.
• Experience with both batch and streaming data processing.
• Ability to build custom Python services and server-to-server API integrations (e.g. FastAPI).
• Understanding of data modeling for analytics — including star schema and lakehouse/medallion (bronze/silver/gold) design patterns.
• Experience with Jira or similar project management tools.

Will be a plus
 

• Familiarity with containerization (Docker); Kubernetes.
• Experience integrating CRM or third-party SaaS platforms via their APIs (e.g. HubSpot, Salesforce) — building bidirectional data syncs, handling webhooks, and reconciling records across systems.
• Change Data Capture (CDC) experience for near-real-time replication.
• Stream processing (Apache Flink, Dataflow) and open table formats (Apache Iceberg).
• Owning data platform architecture end-to-end — technology selection and implementation standards.
• Experience with MySQL.

Duties and responsibilities
 

• Build and maintain infrastructure for reliable extraction, transformation, and loading of data from a variety of sources.
• Design and build batch and streaming pipelines that meet business requirements.
• Own the design and delivery of a bidirectional sync between our production systems and our CRM.
• Conduct SQL performance tuning for existing queries in cloud databases (primarily BigQuery).
• Create and maintain optimized data models and schemas (including star schema and medallion layers) for analytics.
• Evaluate data for integrity and accuracy; work with teams to backfill gaps where found.
• Design and implement data security and governance measures.
• Collaborate with analysts to improve data collection and processing.
• Work with stakeholders on data-related technical issues and support their infrastructure needs.
• Participate in strategic, data-related decision-making.

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

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 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: 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: 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

We are seeking an experienced Data Engineer to develop and support reliable data infrastructure across our systems. In this role, you will create scalable data pipelines, maintain data accuracy and consistency, and connect external data sources. Your main goal will be to ensure smooth data movement and strengthen analytics capabilities throughout the organization. You will also help shape our data architecture, apply engineering best practices, and work closely with cross-functional teams to transform raw data into meaningful, actionable insights.

Requirements

• 5+ years of commercial experience in Data Engineering
• Experience gathering business requirements and communicating with stakeholders
• Strong knowledge of Data Warehouse (DWH) architecture and principles
• Hands-on experience designing data warehouses and building ETL pipelines
• Deep practical experience with Python
• Hands-on experience in one or more of the following areas: data processing using PySpark, Apache Spark, Pandas, or similar frameworks; data scraping; integration of third-party data sources and APIs
• Proficiency in SQL and relational databases such as PostgreSQL and MySQL
• Hands-on experience with column-oriented databases such ClickHouse, Snowflake, Cassandra, BigQuery (many tables with millions of records and above each)
• Solid understanding of software design patterns, algorithms, and data structures
• Intermediate English proficiency

Will be a plus

• Experience with messaging platforms such as RabbitMQ or Kafka
• Familiarity with DataOps practices and data pipeline automation
• Familiarity with CI/CD pipelines and Kubernetes environments
• Background in FinTech or Trading domains

Responsibilities

• Communicate with technical and non-technical stakeholders to gather and clarify business requirements
• Review and analyze data and business logic to ensure consistency, accuracy, and reliability
• Design, implement, and maintain data pipelines for efficient and scalable data processing
• Integrate, maintain, and support data solutions and third-party data sources
• Research and evaluate third-party tools, services, and components for potential use
• Follow engineering best practices, including code reviews, testing, refactoring, and continuous delivery
• Design, optimize, and maintain data storage solutions

What we offer:

• Tax expenses coverage for private entrepreneurs in Ukraine
• Expert support and guidance for Ukrainian private entrepreneurs
• 20 paid vacation days per year
• 10 paid sick leave days per year
• Public holidays as per the company’s approved Public holiday list
• Medical insurance
• Opportunity to work remotely
• Professional education budget
• Language learning budget
• Wellness budget (gym membership, sports gear and related expenses)

We are seeking an experienced Data Engineer to develop and support reliable data infrastructure across our systems. In this role, you will create scalable data pipelines, maintain data accuracy and consistency, and connect external data sources. Your main goal will be to ensure smooth data movement and strengthen analytics capabilities throughout the organization. You will also help shape our data architecture, apply engineering best practices, and work closely with cross-functional teams to transform raw data into meaningful, actionable insights.

Requirements

• 3+ years of commercial experience in Data Engineering
• Experience gathering business requirements and communicating with stakeholders
• Strong knowledge of Data Warehouse (DWH) architecture and principles
• Hands-on experience designing data warehouses and building ETL pipelines
• Deep practical experience with Python
• Hands-on experience in one or more of the following areas: data processing using PySpark, Apache Spark, Pandas, or similar frameworks; data scraping; integration of third-party data sources and APIs
• Proficiency in SQL and relational databases such as PostgreSQL and MySQL
• Hands-on experience with column-oriented databases such ClickHouse, Snowflake, Cassandra, BigQuery (many tables with millions of records and above each)
• Solid understanding of software design patterns, algorithms, and data structures
• Intermediate English proficiency

Will be a plus

• Experience with messaging platforms such as RabbitMQ or Kafka
• Familiarity with DataOps practices and data pipeline automation
• Familiarity with CI/CD pipelines and Kubernetes environments
• Background in FinTech or Trading domains

Responsibilities

• Communicate with technical and non-technical stakeholders to gather and clarify business requirements
• Review and analyze data and business logic to ensure consistency, accuracy, and reliability
• Design, implement, and maintain data pipelines for efficient and scalable data processing
• Integrate, maintain, and support data solutions and third-party data sources
• Research and evaluate third-party tools, services, and components for potential use
• Follow engineering best practices, including code reviews, testing, refactoring, and continuous delivery
• Design, optimize, and maintain data storage solutions

What we offer:

• Tax expenses coverage for private entrepreneurs in Ukraine
• Expert support and guidance for Ukrainian private entrepreneurs
• 20 paid vacation days per year
• 10 paid sick leave days per year
• Public holidays as per the company’s approved Public holiday list
• Medical insurance
• Opportunity to work remotely
• Professional education budget
• Language learning budget
• Wellness budget (gym membership, sports gear and related expenses)

Join an exciting journey to create a cutting-edge Consumer Data Lake for a leading global organization based in Europe. This platform will unify, process, and leverage consumer data from various systems, unlocking advanced analytics, insights, and personalization opportunities. As a Senior Data Engineer, you will play a pivotal role in shaping and implementing the platform's architecture, focusing on hands-on technical execution and collaboration with cross-functional teams.

Your work will transform consumer data into actionable insights and personalization on a global scale. Using advanced tools to tackle complex challenges, you’ll innovate within a collaborative environment alongside skilled architects, engineers, and leaders.

Key Responsibilities:

• Hands-On Development: Build, maintain, and optimize data pipelines for ingestion, transformation, and activation.
• Create and implement scalable solutions to handle diverse data sources and high volumes of information
• Data Modeling & Warehousing: Design and maintain efficient data models and schemas for a cloud-based data platform.
• Develop pipelines to ensure data accuracy, integrity, and accessibility for downstream analytics.
• Collaboration: Partner with Solution Architects to translate high-level designs into detailed implementation plans.
• Work closely with Technical Product Owners to align data solutions with business needs.
• Collaborate with global teams to integrate data from diverse platforms, ensuring scalability, security, and accuracy.
• Platform Development: Enable data readiness for advanced analytics, reporting, and segmentation.
• Implement robust frameworks to monitor data quality, accuracy, and performance.
• Testing & Quality Assurance: Implement robust security measures to protect sensitive consumer data at every stage of the pipeline
• Ensure compliance with data privacy regulations (e.g., GDPR, CCPA ..) and internal policies.
• Monitor and address potential vulnerabilities, ensuring the platform adheres to security best practices.

Requirements:

• Over 4+ years of experience showcasing technical expertise and critical thinking in data engineering.
• Hands-on experience with DBT and strong Python programming skills.
• Proficiency in Snowflake and expertise in data modeling are essential.
• Demonstrated experience in building consumer data lakes and developing consumer analytics capabilities is required.
• In-depth understanding of privacy and security engineering within Snowflake, including concepts like RBAC, dynamic/tag-based data masking, row-level security/access policies, and secure views.
• Ability to design, implement, and promote advanced solution patterns and standards for solving complex challenges.
• Familiarity with multiple cloud platforms (Azure or GCP preferred, with a focus on Azure).
• Practical experience with Big Data batch and streaming tools.
• Competence in SQL, NoSQL, relational database design (SAP HANA experience is a bonus), and efficient methods for data retrieval and preparation at scale.
• Proven ability to collect and process raw data at scale, including scripting, web scraping, API integration, and SQL querying.
• Experience working in global environments and collaborating with virtual teams.
• A Bachelor’s or Master’s degree in Data Science, Computer Science, Economics, or a related discipline.

We are expanding our talent pool of Python Data Engineers to support upcoming international projects across various industries, including FinTech, Healthcare, Retail, Logistics, and SaaS.

While there is no immediate project assignment, selected candidates will become part of our network and will be among the first to be considered when new opportunities matching their expertise become available.

Our data engineering projects typically involve designing scalable data pipelines, building ETL/ELT processes, integrating multiple data sources, and developing modern cloud-based data platforms using Python and industry-leading technologies.

We're looking for a Middle+ Data/Databricks Engineer to join our data team and take ownership of pipelines built on Databricks. You'll design and run production-grade ETL/ELT workloads, work with the lakehouse (Delta Lake) architecture, and partner closely with analysts, data scientists, and business stakeholders who rely on the data you deliver. "Middle+" here means roughly 3–5 years of hands-on data engineering experience: you can own a pipeline end to end with minimal supervision, make sound design decisions, and are starting to mentor more junior engineers — without yet carrying full architectural ownership of the platform.

Contract & Logistics

• Contract type: B2B (valid Czech IČO / trade license required).
• Location: Remote, candidate must be based in the Czech Republic; occasional visit to Prague office.
• Start date: ASAP
• English: Fluent 
• Czech: Native/Fluent 

What You'll Do

• Design, build, and maintain scalable ETL/ELT pipelines on Databricks using PySpark and SQL.
• Implement and evolve Delta Lake tables following a medallion (bronze/silver/gold) architecture.
• Develop batch and, where needed, streaming data processing jobs (Structured Streaming).
• Build and maintain CI/CD for Databricks notebooks and jobs (Databricks Asset Bundles, Repos, Git-based workflows).
• Orchestrate pipelines with Databricks Workflows, Azure Data Factory, Airflow, or similar tools.
• Monitor job performance and cluster costs; troubleshoot failures and optimize for reliability and spend.
• Implement data quality checks, testing, and monitoring for critical datasets.
• Collaborate with analysts, data scientists, and business stakeholders to translate requirements into data models.
• Participate in code reviews, document technical decisions, and help shape engineering best practices.
• Provide guidance and informal mentorship to junior team members.

What We're Looking For

• 3+ years of hands-on experience with Apache Spark, ideally on Databricks specifically.
• Strong PySpark and SQL skills, including performance tuning of Spark jobs.
• Practical experience with Delta Lake and lakehouse architecture concepts.
• Solid grasp of data modeling (dimensional modeling, star schema) and ETL/ELT design patterns.
• Experience with at least one major cloud platform — Azure, AWS, or GCP (Azure Databricks is a plus).
• Familiarity with pipeline orchestration tools (Databricks Workflows, ADF, Airflow, or equivalent).
• Working knowledge of Git and CI/CD practices for data engineering.
• Understanding of data governance, access control, and security basics (Unity Catalog is a plus).
• Good written and spoken English; Czech or Slovak is a plus but not required.
• Comfortable working independently and communicating clearly in a remote, distributed team.

Nice to Have

• Databricks certification (Data Engineer Associate or Professional).
• Experience with streaming technologies such as Kafka or Azure Event Hubs.
• Experience with dbt for transformation and testing.
• Solid Python software-engineering practices — testing, packaging, typing.
• Infrastructure-as-code experience (Terraform).
• Exposure to MLOps or ML pipeline support.
• Experience in a regulated or large enterprise data environment.

What We Offer

• Fully remote work with flexible hours, based anywhere in the Czech Republic.
• Long-term B2B cooperation with a stable pipeline of work.
• A modern, actively evolving data stack rather than legacy maintenance work.
• Direct collaboration with senior engineers and architects — real input on design decisions.
• Budget for training, certifications, and conference attendance.
• A flat structure with fast decision-making and minimal bureaucracy.