Top Data Engineer Jobs in Poland

The Senior Data Engineer will design and maintain scalable data pipelines, develop real-time processing systems, and enhance the company's data architecture using AWS and other technologies.

Develop software for risk data pipelines, collaborating with trading teams to manage trade data, improve capital efficiency, and automate operations.

Hands-on lead software engineer building scalable, testable data systems and pipelines using Python, Spark and AWS. Drive engineering excellence, influence architecture, coach engineers, and help evolve a modern lakehouse architecture while translating business problems into pragmatic technical solutions.

Design, build, and maintain large-scale batch and real-time data pipelines for high-volume advertising data using Java/Scala/Python with Spark and Flink. Ensure data quality, optimize performance, improve observability, integrate external sources, and contribute to platform architecture and cross-team design reviews.

Design and implement the Price Optimizer's decision logic: translate pricing rules into mathematical models and production-ready Python code, develop and tune simulation and optimization algorithms, write tested maintainable code, analyze model behavior and edge cases, and collaborate with solution architects and data and engineering teams to integrate models into Dagster pipelines.

Design and implement the Price Optimizer decision logic: translate pricing rules into mathematical models and production-ready Python code, refine simulation and optimization algorithms, write tested maintainable code, validate model behavior, and collaborate with Solution Architects and Data Engineers to integrate into Dagster pipelines.

Design and implement decision-making logic for a price optimizer: translate pricing rules into mathematical models and production-ready Python code, refine simulation and optimization algorithms, validate model behavior using data, and collaborate with architects and data engineers for pipeline integration.

The Technical Support Engineer II will troubleshoot and resolve customer issues related to digital communications systems, while supporting internal/external communication and management of customer expectations.

The Senior Data Engineer will design and optimize scalable data pipelines using Snowflake, ensuring data quality and mentoring junior engineers while implementing best practices.

The Senior Data Engineer will design and evolve the internal Data Platform, focusing on architecture, data engineering, and mentoring while ensuring standards for data quality and governance.

Build and maintain high-throughput data pipelines, design schemas and data models, implement IaC and CI/CD, collaborate with Data Science/AI on feature stores and MLOps, monitor containerized systems, and advise stakeholders on data architecture.

Develop and enhance BI solutions using SAP technologies, ensuring best practices in performance, data integration, and training users on SAP Data & Analytics.

Develop and maintain a cloud-native data ecosystem focusing on metadata management and data quality, integrating solutions with analytical tools, and collaborating with various teams.

The Senior Data Engineer will design, maintain, and optimize data pipelines using Azure Data Factory and dbt while ensuring data quality and integrity.

Lead development and maintenance of OLAP ETL pipelines using PL/SQL, AWS Glue (Python), and Amazon Redshift. Serve as the Oracle database expert supporting Java and data science teams, write and maintain SQL/PLSQL code, and apply AI-assisted development practices.

This role involves designing data architecture, building data transformation pipelines, and maintaining Power BI and Azure solutions. You will ensure data quality and support business intelligence reporting.

Lead a team of data platform engineers to design scalable data pipelines and analytical workflows while driving architectural decisions and ensuring software engineering best practices.

The Research Engineer will build and scale data infrastructure, architect multi-cluster orchestration, and enhance storage systems for AI training platforms.

Lead data platform governance by defining Policy-as-Code standards, automating checks (Governance-as-Code), auditing platform health and costs, reporting to leadership, and enabling engineering teams on secure, compliant platform usage.

Own and evolve a GCP-native data platform from ingestion to reporting. Lead architecture, reliability, observability, data quality, cost optimization, and AI-assisted engineering practices while mentoring engineers and collaborating with product and customer teams.

As a Senior Data Engineer, you'll design, implement, and maintain a Hadoop-based data platform, focusing on data pipelines, collaboration with international teams, and industry standards in data management.

Design and operate scalable, near-real-time data pipelines and backend services for a global payments platform. Model transactional ledger data for reconciliation, ensure data quality and observability, and own systems end-to-end in a remote-first environment.

Lead design and implement CDC-based data architecture (Postgres -> Kafka -> Snowflake). Build streaming/near-real-time pipelines, data quality controls, data contracts, tenant separation, replay/reload mechanisms, and external delivery. Start hands-on and grow a small data engineering team; deliver a pragmatic 3/6/12-month roadmap.

Design, develop, and deploy production-grade ML and AI solutions including LLM fine-tuning, RAG architectures, NLP pipelines, time-series forecasting, supplier risk and anomaly detection, scalable data pipelines, and RESTful integrations with enterprise systems.

The Data Engineer role focuses on developing predictive models and enhancing data engineering practices to support business objectives. Responsibilities include writing clean code, model evaluation, and collaboration with a global team to improve reporting and campaign management.