Data Quality Automation Engineer
Location: Poland
Department: Innovation Group: SPB Implementation Team
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
- Personalized career growth
- Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
- Active tech communities with regular knowledge sharing
- Education reimbursement
- Memorable anniversary presents
- Corporate events and team buildings
- Other location-specific benefits
*not applicable for freelancers
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