Data Quality Automation Engineer

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