Jobs Data Engineer

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

ABOUT THE CLIENT

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

ABOUT THE ROLE

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

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

RESPONSIBILITIES

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

REQUIRED QUALIFICATIONS

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

DESIRED SKILLS

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

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

ABOUT THE CLIENT

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

ABOUT THE ROLE

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

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

RESPONSIBILITIES

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

REQUIRED QUALIFICATIONS

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

DESIRED SKILLS

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

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

ABOUT THE CLIENT

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

ABOUT THE ROLE

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

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

RESPONSIBILITIES

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

REQUIRED QUALIFICATIONS

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

DESIRED SKILLS

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

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

ABOUT THE CLIENT

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

ABOUT THE ROLE

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

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

RESPONSIBILITIES

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

REQUIRED QUALIFICATIONS

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

DESIRED SKILLS

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

We are looking for a strong Senior iOS Developer to help us build and evolve a communications platform. The role is ideal for someone with deep Swift / iOS experience who can take ownership of complex features, contribute to technical decisions, and work effectively within a large cross-functional team.
 

What you’ll do
 

• Design, develop, and maintain the company's iOS application
• Design and implement core features and modules from requirements through production
• Contribute to the technical design and architecture of the application
• Ensure high standards of performance, quality, responsiveness, and UX
• Debug complex technical issues and identify reliable solutions
• Collaborate with cross-functional teams to define, design, and deliver new features
• Write clean, maintainable, and scalable code
• Participate in code reviews and ensure adherence to engineering standards
• Stay up-to-date with modern iOS technologies, tools, and best practices
• Participate in the full software development lifecycle, including planning, development, testing, and deployment
   

What we’re looking for
 

• 5+ years of commercial iOS development experience
• Advanced knowledge of Swift
• Deep hands-on experience with iOS application development, including architectures, design patterns, SDKs, and development tools
• Strong understanding of asynchronous server communication and client-server architecture
• Experience optimizing application performance and UX
• Strong debugging and troubleshooting skills for complex systems
• Experience leading, planning, and executing development of core iOS features and modules
• Ability to navigate complex requirements and collaborate effectively within a large cross-functional team
• Strong problem-solving skills and ability to drive complex tasks through to completion
• Experience working in an Agile development environment
• Fluent English, both written and spoken
   

Nice to have
 

• Experience with SwiftUI
• Familiarity with GitHub Actions, Fastlane, or similar automation tools
• Experience mentoring and onboarding junior iOS developers
• Experience working on communications or real-time applications
   

Why this role
 

• You’ll work on a long-term communications platform with an established client
• You’ll work on complex iOS features used in a real production product
• You’ll have ownership over core application functionality and technical decisions
• Opportunity to work within a large cross-functional team and contribute to the evolution of the product

Join the Dataforest Team!

We are actively expanding our team and looking for strong new talent to join our ranks. If you are a Data Engineer seeking a friendly team, a healthy working environment, and a flexible schedule — you have found the right place to send your CV!

You'll be a great fit if you have:

- 2+ years of experience with Python;
- 2+ years of experience as a Data Engineer;
- Experience with Pandas;
- Experience with SQL DB / NoSQL (Redis, Mongo, Elasticsearch) / BigQuery;
- Familiarity with Amazon Web Services;
- Experience with Kafka;
- Knowledge of data algorithms and data structures is a MUST;
- Working with high volume tables 10m+.

What you'll do:

- Create ETL pipelines and data management solutions (API, Integration logic);
- Different data processing algorithms;
- Involvement in creation of forecasting, recommendation, and classification models.

Would be a plus:

- Experience with Spark (pyspark);
- Experience with Airflow;
- Experience in statistics;
- Knowledge of DS and Machine learning algorithms.

We ensure your growth with:

- Great networking opportunities with international clients, challenging tasks;
- Building interesting projects from scratch using new technologies;
- Personal and professional development opportunities;
- Competitive salary fixed in USD;
- Paid vacation and sick leaves;
- Flexible work schedule;
- Friendly working environment with minimal hierarchy;
- Team building activities, corporate events.

Client

Our client is the UK’s leading development finance institution, dedicated to supporting companies in developing countries and driving sustainable growth.

Position overview

We are looking for a Senior/Lead Data Engineer to join a distributed team working on modern cloud-based data solutions within the Azure ecosystem. The role involves designing, developing, and maintaining scalable data pipelines and integrations that support business-critical reporting, analytics, and operational processes.

You will work closely with cross-functional teams, contributing to architecture decisions, delivery processes, and continuous platform improvements while ensuring high standards of quality and reliability.

Responsibilities

• Design, develop, and maintain data pipelines and ETL/ELT processes using Azure technologies
• Build and support scalable solutions using Azure Data Factory (ADF), Azure SQL, and other Azure services
• Develop backend logic and automation using Python, Azure Functions, and Logic Apps
• Collaborate with stakeholders, analysts, and engineering teams to gather requirements and deliver data solutions
• Monitor, troubleshoot, and optimize data workflows and integrations
• Participate in code reviews, technical discussions, and solution design activities
• Contribute to CI/CD and deployment processes within the Azure environment
• Ensure data quality, security, and performance best practices are followed
   

Requirements

• Strong hands-on experience with Azure Data Factory (ADF)
• Solid experience with Azure SQL and the Azure Data Stack
• Strong Python development skills
• Experience working with Azure Logic Apps and Azure Function Apps
• Good understanding of cloud-based data architecture and integration patterns
• Experience building and maintaining scalable data pipelines
• Familiarity with Azure DevOps, Git, and CI/CD pipelines
• Experience working in Agile development environments
• Strong communication and collaboration skills
• Upper-Intermediate or higher English level

Nice to have

• Experience leading technical initiatives or mentoring engineers
• Knowledge of data governance and security best practices
• Experience with infrastructure automation or monitoring tools
• Exposure to financial services or development finance domains

Our client is looking for a Data Engineer.

Role Overview:Our client is looking for a Data Engineer to help them develop and maintain their data platform. Their infrastructure is primarily AWS-based, with Airflow, S3 and Redshift at its core, alongside a legacy stack based on MS SQL Server, SSIS and custom Python scripts. You will work on building reliable data pipelines, improving data infrastructure, and gradually modernising legacy processes.Key Responsibilities:

• Design, develop and maintain scalable and reliable data pipelines and ETL/ELT processes;
• Develop and optimise data warehouse solutions;
• Develop and maintain data infrastructure, primarily on AWS, while also supporting parts of our legacy infrastructure;
• Develop APIs and data integrations;
• ontribute to the development and maintenance of real-time data pipelines using Kafka;
• Automate and optimise data processes and workflows;
• Monitor, troubleshoot and improve the reliability, performance, security and data quality of pipelines and infrastructure;
• Work closely with the analytics team and other stakeholders to understand their data needs and deliver effective solutions;
• Maintain clear and up-to-date documentation for data pipelines, infrastructure and workflows;
• Contribute to the improvement and modernisation of existing data processes and architecture.

Required Skills & Experience:

• 2+ years of professional experience in data engineering;
• Strong SQL and Python skills;
• Hands-on experience with AWS, including S3, Redshift, Glue and Lambda;
• Hands-on experience with Apache Airflow;
• Strong understanding of data warehousing concepts and data modelling;
• Hands-on experience designing, developing and maintaining production data pipelines, with a focus on reliability, monitoring and data quality;
• Solid understanding of relational and non-relational databases;
• Familiarity with Git and CI/CD practices, preferably GitLab;
• Experience developing APIs and data integrations;
• Kafka and real-time data processing experience is a plus;
• MS SQL Server and SSIS experience is a plus;
• Good written and verbal communication skills;
• Upper-intermediate English or higher.

The company guarantees you the following benefits:

• A positive workplace atmosphere that creates a culture of collaboration and support, making it a place you'll love working in;
• Competitive compensation and regular career development reviews;
• Flexible working hours and remote working options, you'll enjoy the freedom that the company provides;
• A generous vacation and sick leave policy, allowing you to take time off and enjoy a work-life balance;
• Financial assistance for professional development, helping you stay ahead of the curve and love your career path;
• Educational Allowances that give you the opportunity to expand your knowledge and experience;
• You'll have a monthly allowance for personal activities, giving you the opportunity to pursue your interests and hobbies outside of work;
• A comprehensive health insurance plan, depending on your current location;
• Referral program with financial rewards for bringing top talent to the company;
• Engaging in team-building activities and corporate parties.

Interview process:

• HR Interview with the Recruiter;
• Techincal inetrview;
• Final interview with the team.

If you find this opportunity right for you, don't hesitate to apply or get in touch with us if you have any questions!

Job Description

• Extensive hands-on experience in IAM data and configuration migration, particularly involving complex user assignments and request histories.
• Proficiency in rebuilding and verifying Joiner, Mover, and Leaver (JML) access workflows.
• Experience migrating role-based access metadata and system entitlements across hundreds of target applications.
• Strong capability in executing trial migration runs, performing data reconciliation, and remediating deprecated features.
• Ability to generate operational runbooks and conduct technical knowledge transfer sessions for internal IT operations teams.
• Experience and strong knowledge of Identity Governance and Identity Lifecycle Management
• Deep expertise in Identity and Access Management (IAM) systems, with direct experience configuring and upgrading Bravura Identity.
• Strong technical background in integrating and provisioning to Active Directory (AD) and Microsoft Exchange.

Job Responsibilities

The IAM Migration Engineer is responsible for the accurate, complete, and secure transfer of all data, settings, and configurations from the legacy Bravura Identity system to the new supported version. This role is critical for maintaining the integrity of historical data and ensuring the uninterrupted functionality of existing access provisioning processes (joiners, movers, leavers).

• Execute the full migration of user data for 559 users.
• Migrates and verifies 58 configured workflows
• Transfers roles and entitlements that govern access across 221 applications.
• Migrate the complete request history, ensuring that absolutely no data is lost.
• Participates in trial migration runs and data reconciliation to guarantee a flawless transition into the production environment.

Department/Project Description

The project focuses on transitioning the Bravura Identity management platform to a newly supported version for a leading banking and financial institution. The process includes standing up non-production environments for change rehearsals (including a rehearsed cutover with rollback capabilities) and executing a full data migration without altering the underlying architecture. 

We are looking for a Data Engineer to join our team and play a key role in building scalable, reliable, and business-focused data products from the ground up. This is a great opportunity to contribute to the development of core data infrastructure, influence technical decisions, and help establish best practices in data engineering across the organization.

Responsibilities:

• Build data engineering products (data models, pipelines, data quality automations, monitoring), end-to-end ownership of data products.
• Collaborate closely with data analysts, PMs, and stakeholders on both new and existing data products

• Apply best engineering CI/CD practices to data workflows and processes

   

Requirements:

• 3+ years of experience in Data Engineering, Analytics Engineering, or a related field
• Strong knowledge of SQL, Python, and dbt
• Hands-on experience with ELT/ETL, data quality, and analytics engineering
• Experience working with cloud platforms such as AWS, GCP, or Azure

• Experience with cloud data warehouses such as Databricks, Snowflake, BigQuery, Redshift, or similar

   

Nice to have:

• Strong attention to automation
• DevOps background
• Product engineering mindset (focus on business impact, not just data engineering)
• Experience with BI tools and delivering impactful analysis

What you'll be doing

• Own the lakehouse architecture: bronze/silver/gold layers, Iceberg/Delta tables, schema evolution.
• Land operational data via CDC streaming (Kafka, Debezium), handling late and duplicate events.
• Design data layout for speed and cost: partitioning, compaction, file sizing, query performance on Trino/Athena/Snowflake.
• Own retention and archival: storage tiering, regulatory retention, immutability, GDPR deletion.
• Guarantee correctness: freshness SLAs, drift detection, reconciliation against the source wallet and ledger systems.
• Own governance: catalog and lineage, row/column access control, PII masking, encryption, audit trails.
• Monitor ingestion health, data anomalies, and cloud storage/compute spend.

Must-have

• Senior: 5+ years in data engineering, with real ownership of a large-scale data lake or lakehouse.
• Lakehouse architecture — bronze/silver/gold layering, an open table format (Iceberg, Delta, or Hudi), schema evolution.
• Data layout & query optimization at TB+ scale — partitioning, compaction, file sizing, query performance on Trino/Athena/Snowflake.
• Cloud lakehouse/DWH in production — Snowflake, Databricks, or BigQuery.
• CDC & streaming ingestion — Kafka + Debezium or equivalent; late, duplicate and out-of-order events.
• Strong SQL and data modeling — enough relational grounding to reason about the OLTP systems you capture from. Critical for financial ledgers.
• Correctness — freshness SLAs, drift detection, reconciliation against source wallet/ledger systems.
• Governance — catalogs, lineage, row/column access control, PII masking, retention, GDPR deletion.
• Cloud object storage — S3 or GCS, plus storage tiering and archival.
• Python and an orchestrator — Airflow or Dagster, as tools.

Location & work model

Kraków, Poland. Hybrid — 2 days per week from the office.

We are looking for AVEVA PI System Engineers at Middle and Senior levels to join our team and work on industrial data solutions for international customers.

You’ll work with the AVEVA PI System ecosystem, helping customers collect, structure, contextualize, analyze, and get value from operational data.

Depending on your experience, you can contribute as a PI System Engineer or take ownership of technical delivery as a Senior Engineer.
 

What you’ll do

• Implement, configure, maintain, and support AVEVA PI System solutions.
• Work with industrial operational data and help structure it into meaningful, reliable information.
• Design and develop Asset Framework (AF) structures and information models.
• Work with Event Frames, PI Analytics, calculations, and data contextualization.
• Troubleshoot technical issues and support PI System environments in production.
• Contribute to PI System implementations, upgrades, migrations, and optimization projects.
• Create technical documentation, reusable templates, standards, and best practices.
• Collaborate with engineers, consultants, and customers to deliver reliable and scalable solutions.
   

For PI System Engineer

We’d expect you to have:

• 2+ years of hands-on experience with AVEVA PI System in application support, implementation, or technical project delivery.
• Good understanding of PI System concepts, including Asset Framework, information modelling, calculations, data contextualization, and operational data integration.
• Experience troubleshooting and supporting PI System environments.
• Ability to work independently while knowing when to involve more experienced colleagues.
• Interest in developing towards a customer-facing PI System consulting role.
   

For Senior PI System Engineer

In addition to the above, you should have:

• 5+ years of hands-on experience implementing, configuring, optimizing, and supporting AVEVA PI System solutions in production environments.
• Strong expertise in Asset Framework, information modelling, Event Frames, PI Analytics, and scalable/reusable PI System data models.
• Experience leading complex implementations, upgrades, migrations, or performance optimization initiatives.
• Ability to independently troubleshoot complex technical issues in business-critical PI System environments.
• Experience acting as a Technical Lead or taking technical ownership of PI System projects.
• Ability to define and promote technical standards, implementation approaches, and best practices.
   

What we offer

• International projects in the industrial / operational technology domain.
• Opportunity to work with experienced PI System professionals and develop your expertise.
• A chance to grow towards a consulting or technical leadership role.
• Remote-first work environment.
• Challenging projects where industrial data and technology have a real business impact.
   

If you have strong AVEVA PI System experience and are looking for your next technical challenge, we’d be happy to hear from you.

Automat-it is an all-in AWS Premier Partner and Managed Services Provider specializing in the startup ecosystem. With over 800 customers and 500+ AWS certifications, Automat-it brings hands-on expertise in AI, DevOps, and FinOps to empower fast-paced startups to grow, deliver & win. Our customers save significant time-to-market and optimize their cloud performance and costs.

We work across EMEA and the US, fueling innovation and solving complex challenges daily. Join us to grow your skills, shape bold ideas, and help build the future of tech.

We’re looking for a Senior Data Engineer to join our growing Data & Analytics practice and build modern data solutions for our customers on AWS.

This is a highly hands-on engineering role. You’ll work across different customer environments and data challenges, from modernizing legacy pipelines and building lakehouse platforms to optimizing analytical workloads and owning smaller data platforms end-to-end.

You won’t be limited to one stack or one long-running product. One project may involve Spark and Apache Iceberg, another Redshift performance and data modeling, and another Kafka, OpenSearch, or a new data platform built from ingestion through analytics.

We’re looking for someone who can take ownership of a data engineering problem, make sound technical decisions, and deliver independently without needing constant direction.

📍 Work location: Ukraine, remote

If you are interested in this opportunity, please submit your CV in English.

Responsibilities

• Design, build, and optimize production data pipelines and data platforms on AWS.
• Build scalable data processing workloads using Spark/PySpark, Python, and SQL.
• Build and modernize data lakes and lakehouse architectures, working with technologies such as Amazon S3, Apache Iceberg, AWS Glue, and related data services.
• Design, troubleshoot, and optimize analytical workloads and data warehouses, including Amazon Redshift and other OLAP platforms.
• Modernize legacy and inefficient data workloads, including moving existing ETL/ELT processing to scalable distributed data architectures.
• Work with streaming and event-driven data pipelines using technologies such as Kafka, Kinesis Data Firehose, and related services.
• Investigate real production data problems, from performance bottlenecks and data modeling issues to upstream/downstream dependencies, and recommend practical solutions.
• Take ownership of customer projects end-to-end, from understanding the technical problem through implementation, testing, and delivery.
• Work directly with customers when needed to clarify requirements, explain technical decisions, and recommend solutions based on your expertise.
• Build data foundations for analytics and ML workloads, collaborating with Data Scientists, DevOps, and MLOps engineers.
• Contribute to dashboards and analytics when required using QuickSight or other BI tools.

• Apply practical engineering practices around data quality, testing, CI/CD, security, governance, and infrastructure automation.

   

Requirements

• Strong production experience in Data Engineering, with the ability to independently own and deliver data projects.
• Deep hands-on experience with Apache Spark / PySpark and distributed data processing.
• Strong Python and SQL skills.
• Hands-on experience building data solutions on AWS.
• Strong understanding of data lakes, lakehouse architectures, ETL/ELT, data modeling, and data processing at scale.
• Experience with analytical databases and data warehouses. Strong Amazon Redshift experience is highly valuable; deep experience with platforms such as Snowflake, Synapse, or similar OLAP technologies is also relevant.
• Understanding of streaming architectures and technologies such as Kafka or Amazon Kinesis.
• Ability to troubleshoot existing data systems, understand how data flows across upstream and downstream components, and improve performance and reliability.
• Ability to work autonomously, make pragmatic technical decisions, and take responsibility for delivery.

• Good communication skills and the ability to discuss technical problems and solutions directly with customers in English.

   

Nice to have

• Experience with Apache Iceberg or other modern open table formats and lakehouse technologies.
• Amazon OpenSearch Service / Elasticsearch experience.
• Experience with BI and visualization tools such as Amazon QuickSight, Tableau, or Power BI.
• Terraform and Infrastructure as Code.
• CI/CD practices for data pipelines, including data testing and validation.
• Experience preparing data platforms for ML workloads using services such as Amazon SageMaker.
• Exposure to Amazon Bedrock, GenAI, or agentic development.

• Experience with Databricks, Snowflake, ClickHouse, or other modern data platforms

   

What Success Looks Like in Year One

• Independently owns assigned data projects end-to-end, from understanding the problem and making technical decisions to implementation, troubleshooting, testing and successful delivery, with minimal supervision.
• Has built strong practical expertise across the team’s core data stack and can confidently work across different customer environments, including Spark, Python/SQL, data lakes/lakehouses, analytical and NoSQL databases, streaming and other technologies used by the team.
• Can investigate unfamiliar data problems independently, identify performance or data-modeling issues, understand upstream/downstream dependencies, and recommend pragmatic solutions to customers.

• Continuously expands technical depth, keeps up with modern Data technologies and patterns, and can quickly learn new technologies as customer projects and the Data practice evolve.

   

Benefits

• Professional training and certifications covered by the company (AWS, FinOps, Kubernetes, etc.)
• International work environment
• Referral program — enjoy cooperation with your colleagues and get a bonus
• Company events and social gatherings (happy hours, team events, knowledge sharing, etc.)
• English classes

• Soft skills training

   

Country-specific benefits will be discussed during the hiring process.

Automat-it is committed to fostering a workplace that promotes equal opportunities for all and believes that a diverse workforce is crucial to our success. Our recruitment decisions are based on your experience and skills, recognising the value you bring to our

The Defense Procurement Agency (DOT) is a national agency responsible for procuring ammunition, UAVs, military equipment, fuel, food, clothing, and other critical supplies for the Armed Forces of Ukraine and the Defense Forces.

Our mission: Strengthening Ukraine by ensuring reliable support for the Defense Forces while fostering the development of the national defense industry.

Our vision: To become the driving force behind the transformation of Ukraine's defense procurement ecosystem—not only operating the system, but continuously improving it.

We are looking for a Head of Data Governance to establish and lead the organization's enterprise Data Governance function. In this role, you will define the vision, policies, standards, and governance framework for managing data across the organization, ensuring high-quality, trusted, and well-governed data that enables informed decision-making and supports large-scale digital transformation initiatives.

Responsibilities

• Lead the design, implementation, and continuous improvement of the organization's Data Governance framework.
• Develop and maintain enterprise-wide data policies, standards, methodologies, and governance processes.
  Establish and enhance Master Data Management (MDM), Reference Data, Metadata Management, and Data Quality practices.
• Define data ownership, stewardship, governance roles, and accountability across business units.
• Develop data quality standards, monitoring processes, and governance controls.
• Collaborate with business stakeholders, analysts, architects, and engineering teams to define enterprise data requirements.
• Contribute to enterprise data models and integration requirements across corporate information systems.
• Prepare governance documentation, methodologies, standards, and best practices.
• Ensure Data Governance principles are embedded into the implementation of new enterprise systems and digital services.
• Build, lead, mentor, and develop the Data Governance team while driving collaboration across the organization.

Requirements

• Bachelor's degree in Information Technology, Applied Mathematics, Economics, Finance, or a related field.
• Proven experience in Data Governance, Data Management, Business Intelligence, Business Analysis, or related disciplines.
• Hands-on experience implementing or improving Data Governance, Master Data Management (MDM), Data Quality, or Metadata Management initiatives.
• Strong understanding of Data Governance principles, data lifecycle management, and enterprise data architecture.
• Experience developing enterprise policies, standards, governance frameworks, or methodological documentation.
• Experience collaborating with business and technology teams to define and implement enterprise data requirements.
• Understanding of enterprise platforms such as ERP, CRM, BI, Data Warehouse, or similar systems.
• Experience leading teams or coordinating cross-functional initiatives.
• Strong analytical thinking, structured problem-solving, and stakeholder management skills.
• English proficiency at Intermediate level or higher.

Nice to Have

• Experience with SQL, Power BI, or other Business Intelligence platforms.
• Experience implementing Business Glossary, Data Catalog, or Metadata Management solutions.
• Knowledge of DAMA-DMBOK, DCAM, or other Data Governance frameworks.
• Experience supporting enterprise digital transformation programs.

What We Offer

• Meaningful work that directly contributes to strengthening Ukraine's defense capabilities.
• Official employment with competitive salary and full social benefits.
• Professional development, learning opportunities, and career growth.
• Structured onboarding and dedicated mentorship.
• A collaborative, supportive, and mission-driven team.
• Modern office near the metro with reliable internet and equipped shelter.
• Opportunity to establish and scale an enterprise-wide Data Governance function within one of Ukraine's most strategically important organizations.

By joining our team, you will contribute to one of Ukraine's largest digital transformation initiatives in the defense sector and help build the future of defense procurement.

Ready to make a real impact? We'd love to hear from you. Apply today!

* By submitting your CV, you consent to the processing of your personal data in accordance with applicable legislation.

** Due to the high volume of applications, only candidates whose qualifications best match the position will be contacted.

We are looking for a senior data engineer with deep Databricks experience to own the data platform behind one of our largest enterprise accounts and lead its migration from AWS to Databricks.

About the role

Data infrastructure is the foundation of everything we deliver. Our models, dashboards, and the decisions our clients make on top of them are only as reliable as the pipelines underneath, which is why we put the platform first.

You will join a small senior team working inside the client's environment. Through the rest of 2026 you will take ownership of the existing pipelines and the architecture around them. From 2027 you will lead the migration to Databricks: designing the target architecture, planning the cutover, and doing the implementation. This is a hands-on engineering role with real architectural authority. You decide how the platform gets built, and then you build it.

You will be the person the team turns to on anything Databricks, working alongside senior machine learning engineers and data scientists who depend on what you deliver.

What you will do:

• Design and build the target Databricks architecture, and plan the migration from the current AWS stack
• Build and maintain production data pipelines: ingestion, transformation, and orchestration
• Own data quality, including the checks and alerts that catch problems before the client does
• Design the data models the analytics and machine learning work sits on
• Support the pipelines you build: monitoring, alerting, and the on-call reality of production data
• Work directly with the client's engineers, and explain technical decisions to people who are not engineers

Requirements:

• Five or more years in data engineering or software development
• At least three years of production Databricks work
• Deep experience with Spark, Delta Lake, and Unity Catalog
• Has planned and executed at least one migration onto Databricks from another platform, and can walk through the challenges
• Expert Python: clean modular code, comfortable with optimization and profiling
• Advanced SQL and relational database work: raw SQL, data modeling, scripted migrations
• Systems design: how storage and compute fit together, end to end pipelines, containerized applications
• Cloud operations on AWS or equivalent: networking, identity and access management, monitoring and alerting, and the domain knowledge for why things break
• Comfortable working inside a client's environment, with their data and their constraints
• Strong written English, and spoken English good enough to present your work
• Available for some overlap with United States working hours

Nice to have:

• Databricks certification
• Deep AWS experience specifically, since that is the platform we are migrating from
• dbt, Airflow, or a similar transformation and orchestration framework
• Machine learning pipeline experience, since models run on top of what you build
• Background in utilities, energy, telecoms, or another regulated industry
• Experience being the senior engineer a client relies on directly

You are:

• Careful with data quality, and you ask when something looks wrong instead of guessing
• A self starter who can turn a general requirement into a specific estimate and a deliverable
• Someone who documents. We write things down, and every number we deliver carries its source
• Comfortable in a small remote team where nobody is checking your hours

About Bennett Data Science

We have spent ten years building predictive analytics and data science for enterprise clients, from some of the largest companies in the world to startups in Silicon Valley. Our engineers sit inside the client's systems and build critical systems. The work ships to production and lands at the bottom line.

What we offer:

• Competitive compensation, reviewed as you grow
• Work from anywhere, with a flexible schedule
• A small senior team, so your work is visible and your decisions are important
• Direct exposure to enterprise clients and the problems they actually have
• Mentorship from senior staff, and the space to grow and mentor others