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