Data Quality Automation Engineer

Data Quality Automation Engineer (#5100) European Union, Poland Work type: Office/Remote Technical Level: Senior Job Category: Quality Control Project: About the project: The Client provides comprehensive operational support and a range of expert services to the world’s leading insurers, brokers, fleet managers, and automotive manufacturers. 3,300 employees across ten countries deliver exceptional standards on a large scale for over 1,200 clients. We help the global insurance market to handle millions of claims each year in the most cost-effective and efficient ways possible. The Client is embarking on an exciting and challenging transformation program, and our software solutions are a driving force behind this strategy, using cloud computing and leading-edge design patterns. Key Responsibilities Define and implement data quality rules across ingestion, transformation, and reporting layers Validate data in Databricks-based pipelines Monitor and test Databricks transformations (PySpark/SQL) for correctness and completeness Ensure Databricks / Power BI reports reflect accurate and reconciled data Set up data validation checks (schema, nulls, duplicates, ranges, referential integrity) Identify, log, and track data quality issues with root cause analysis Collaborate with data engineers and analysts to fix issues Build automated data quality monitoring and alerts Required Skills 4-5+ years of Relevant work experience in data analysis, quality assurance, data governance, or a similar field is highly desirable. Strong knowledge of Databricks / Spark (SQL, PySpark) Understanding of ETL/ELT pipelines and data transformations (dbt) Experience validating BI/reporting outputs (Power BI preferred) SQL proficiency for data validation and reconciliation Familiarity with data quality frameworks/tools (e.g., Great Expectations is a plus) Nice to Have Experience with AWS data stack Experience with data governance or data catalog tools Exposure to CI/CD for data pipelines Knowledge of data lineage and observability tools Success Criteria Reduced data defects in pipelines and reports Automated data quality checks are in place Clear visibility and tracking of data issues We offer*: Flexible working format - remote, office-based or flexible A competitive salary and good compensation package Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more) Active tech communities with regular knowledge sharing Project: Tech solution provider for clinical research #J-18808-Ljbffr