Data Engineer Consultant for EU projects | Poland

Within the Government & Public Sector practice, the team brings deep EU industry expertise to help EU institutions address critical finance, accounting, and reporting challenges during their transformation. This role strengthens the Finance @ EU Center of Excellence.

• Typically, 3-4 years of relevant hands-on experience in data integration, ETL, BI, data transformation, or a related area.
• Solid SQL skills, including writing, analyzing, and troubleshooting queries and working with relational databases.
• Good understanding of ETL/ELT concepts, data integration patterns, and data warehousing (DWH) fundamentals.
• Hands-on experience with data transformation, mapping, validation, and investigation of data quality issues.
• Ability to work independently on clearly defined tasks, investigate problems, and propose solutions.
• Ability to communicate data-related findings and technical concepts clearly to technical and non-technical stakeholders.
• Interest in working with European Union institutions and willingness to travel occasionally to Brussels.
• Master's degree in a relevant field.
• EU Work Permit.

Nice to have:

• Experience with PL/SQL and/or T-SQL.
• Experience with scripting languages such as Python or Shell scripting for data handling or automation.
• Experience with data integration or orchestration tools such as SAP Data Services, Apache Hop, Apache Airflow, or similar.
• Exposure to ERP environments, particularly SAP, or experience working with enterprise-scale data landscapes.
• Experience with data modelling or BI/reporting solutions.

• Design, build, and maintain ETL and data integration workflows connecting multiple internal and external data sources.
• Analyze source data, define mappings and transformation rules, and ensure data quality, consistency, and traceability.
• Investigate data issues, troubleshoot ETL processes, and independently drive clearly defined tasks to resolution.
• Collaborate with data, BI, ERP, and subject matter experts throughout the solution lifecycle, from analysis and modelling to testing, deployment, and continuous improvement.