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Data Quality Automation Engineer

N-iXIkona lokalizacjiGlobalnie

Żródlo publikacji: JustJoin.it
Rodzaj zatrudnienia
Rodzaj zatrudnieniaPełny etat
Doświadczenie
DoświadczenieSenior
Dodano
Dodano15 lipca 2026
Wykryte przez nas
Wykryte przez nas20 lipca 2026
Zarobki
Zarobki4438 - 4761 CHF

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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