Top Data Engineer Jobs in Poland

Design, build, and scale Snowflake-based data products and pipelines to support AI/ML, dashboards, and cross-OpCo analytics. Lead complex, cross-team initiatives, set data modelling and pipeline best practices, implement automated data quality and observability, and maintain uptime, optimization, and compliance.

Design, build, and maintain complex data pipelines and ETL processes; collaborate with product, design, and data science teams; ensure performance, quality, testing, documentation, and mentor junior engineers.

The Staff/Lead Fullstack Engineer will enhance the Mimica Webapp by architecting scalable UI components, managing large datasets, and optimizing performance while collaborating with cross-functional teams.

Seeking a Senior Data Engineer to develop scalable data pipelines, manage AWS data services, optimize ETL processes, and enhance data quality.

The Senior Data Engineer will develop data pipelines, design data models, build ETL/ELT solutions, and implement improvements to the Azure-based Data Analytics Platform.

Seeking a Senior Data Support Engineer with 5-6 years of experience in Data Engineering, specifically utilizing Snowflake, Python, SQL, and AWS for data manipulation, warehousing, and testing processes.

As a Software Engineer Intern, you will design, develop, and test web applications, contribute to research, and collaborate in an Agile team.

The Senior Data Engineer will design and maintain data pipelines, ensuring high data quality and performance. Responsibilities include ETL development, data transformation, and documentation.

The Software Engineer will build scalable, distributed data infrastructure, lead cross-functional initiatives, and contribute to open-source communities.

The Senior QA Engineer develops test strategies, automation, and tools for AI-enhanced software, focusing on data recovery systems and software quality improvement.

The Software Principal Engineer will develop data recovery software, design new features, create documentation, and debug issues in a team-oriented environment.

Design, build, and maintain backend services and automation for data pipelines and internal tooling. Integrate AI/ML features, own CI/CD and observability, lead code reviews, and collaborate with cross-functional teams to ensure scalable, reliable production systems.

Maintain and expand a high-scale data platform: build and run data pipelines, implement DataOps, collaborate with analytics teams, ensure data quality and security, and design enterprise data models.

As a Senior Data Engineer, you will design and implement core systems for data science, create data platforms and pipelines, and leverage AI solutions to aid data-driven decision making.

Lead the design and delivery of scalable cloud-native data platforms, build pipelines and lakehouses, mentor engineers, contribute to architecture, support pre-sales, and engage with stakeholders.

Develop tools and infrastructure for data analysis, automate systems, ensure trading performance, and support CI/CD workflows in a low-latency trading environment.

The Data Platform Lead will design, build, and maintain the data warehouse for a digital bank, ensuring data quality and compliance.

As a Data Engineer, you will develop and maintain ETL data pipelines, ML data pipelines using Temporal, and backend services in Go while ensuring high performance and reliability.

Develop and manage scalable backend platform for analytical models using Python and MLFlow, ensuring data validation and model traceability while collaborating with teams.

The Data Engineer will focus on infrastructure automation, reliability, and cost optimization. Responsibilities include designing Infrastructure-as-Code, managing CI/CD pipelines, establishing observability standards, and collaborating with teams to improve platform resilience.

Design and maintain data pipelines, ensure data reliability, structure data systems, and manage software development processes while collaborating in a team.

Seeking a mid-level Backend Engineer to design and implement scalable backend services and APIs with a focus on cloud infrastructure and data pipelines.

The Data Engineering Application Engineer manages Network Control projects, implements data handling solutions, configures databases, analyzes customer data, and supports technical issues with a focus on customer satisfaction.

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

End-to-end delivery of ML-powered services, involving research, prototyping, production, and operations. Collaborate on product requirements while maintaining high quality and operational excellence.