About the job
About the Role
nix is seeking a Data Quality Automation Engineer to join a team supporting a global client in the insurance and automotive sectors. The client operates across ten countries, serving over 1,200 organizations and managing millions of claims each year. This role contributes to a major transformation program, with a focus on cloud-based software and modern design patterns.
What You Will Do
- Define and maintain data quality rules at all stages: ingestion, transformation, and reporting.
- Validate data in Databricks pipelines.
- Monitor and test Databricks transformations using PySpark and SQL to confirm data accuracy and completeness.
- Check that Databricks and Power BI reports reflect accurate, reconciled data.
- Set up data validation checks for schema, nulls, duplicates, ranges, and referential integrity.
- Identify, document, and analyze data quality issues, including root causes.
- Work closely with data engineers and analysts to resolve issues.
- Develop automated systems for data quality monitoring and alerts.
Requirements
- At least 4-5 years of experience in data analysis, quality assurance, data governance, or a related area.
- Strong knowledge of Databricks or Spark, including SQL and PySpark.
- Experience with ETL/ELT pipelines and data transformation tools (such as dbt).
- Background in validating BI or reporting outputs, with Power BI preferred.
- Advanced SQL skills for data validation and reconciliation.
- Familiarity with data quality frameworks or tools (Great Expectations is a plus).
Bonus Skills
- Experience with AWS data stack.
- Knowledge of data governance or data catalog tools.
- Exposure to CI/CD practices for data pipelines.
- Understanding of data lineage and observability tools.
What Success Looks Like
- Fewer data defects in pipelines and reports.
- Automated data quality checks in place.
- Transparent tracking and visibility of data issues.
Location
This position is based in Poland.
