Top Data Engineer Jobs in Poland

Design and build data pipelines and systems that support AI-driven insights and analytics, collaborating with cross-functional teams.

The Data Platform Engineer will develop and maintain data lakes and pipelines, propose improvements, and ensure best practices in data engineering.

The Data Engineer will migrate legacy data pipelines into the Snowflake and dbt environments, developing Python-based ETL flows and collaborating with cross-functional teams to ensure a scalable data platform.

Design and maintain data pipelines using DBT, optimize models in Snowflake, and develop Streamlit applications with Python while applying software development best practices.

The Data Engineer will develop and optimize data pipelines, improve architectural solutions, and collaborate across teams to deliver data-driven insights.

Design and architect scalable backend services, develop robust governance systems, build SaaS solutions, and mentor junior engineers to enhance IoT platform capabilities.

As a Senior Backend Data Engineer, you'll design large-scale data pipelines, develop backend services, and collaborate with cross-functional teams to enhance digital environments.

The Principal Data Engineer will design, develop, and maintain data products, build scalable data pipelines, and ensure data quality and governance.

As a Data Engineer, you will develop data pipelines, optimize ETL processes, build integrations, and enhance the data analytics platform in Azure.

As a Data Engineer, you will manage PostgreSQL RDS upgrades, implement data archiving strategies, and collaborate with engineering teams for optimal database performance.

As a Data Engineer, your role involves building ETL/ELT workflows, data modeling, team collaboration, and maintaining data quality for analytics in a health-focused company.

As a Senior/Expert ML/Data Engineer, you will build data pipelines and ML models, focusing on AI/ML innovations, mentoring, and optimizing data solutions.

As a Data Engineer, you'll develop and maintain SQL data models, build real-time data pipelines, and collaborate with teams to enhance data modeling and customer insights.

The Senior Customer Integration Engineer analyzes, cleans, and transforms customer data into standardized datasets for integration into business operations.

As a Data Engineer, you'll design and optimize data pipelines on Databricks, implement scalable data models, and collaborate with AI teams for advanced analytics and security integrations.

As a Data Engineer, you'll maintain and configure the Snowflake data platform, design integration pipelines, and innovate with new tools. Your role supports data security and performance while collaborating across teams.

The Junior Data Engineer will analyze data, design experiments, build a marketing data stack, and collaborate with teams to improve data access and insights.

The Data Engineer will analyze and process large datasets, optimize SQL queries, work with Snowflake, and use BI tools for insights, while collaborating with teams to support data-driven decisions.

Design and develop reporting for stakeholders, manage BI initiatives, enhance data warehouse, analyze data structures, and support ad-hoc reports.

Lead the data engineering team, ensuring quality data processes and product stability while managing operational tasks and stakeholder coordination.

The Middle Data Engineer will monitor and manage data pipelines, troubleshoot ETL/ELT failures, optimize queries in BI tools, and address data quality issues.

As a Data Engineer at Nansen, you will build and optimize systems for their customer-facing analytics product, collaborating closely with crypto researchers and engineers to tackle large-scale data challenges and ensure data quality and reliability.

The Data Engineer will build and maintain data infrastructure, manage ETL platforms, ensure data quality, and mentor DevOps teams while collaborating cross-functionally.

The job involves designing and managing scalable data pipelines, collaborating with teams on data infrastructure, and writing efficient code in Python and Scala while ensuring data quality and security.

The Data Engineer will design, develop, and maintain BigQuery data pipelines, optimize performance, troubleshoot data issues, and support data-driven decision-making.