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Data engineering & Databricks / UTIS-QA-US-009

Test Automation Engineer (Azure Data Platform / Databricks)

Own test automation and data validation for a global semiconductor company’s Azure data platform, using Python/PyTest, Databricks and Azure DevOps.

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Region
San Diego, California, United States
Work arrangement
Onsite
Engagement type
Independent contractor with UTIS (1099)
Working hours
Full-time onsite attendance.
Posted
September 30, 2026
Applications
Open until filled

What you will work on

  • Build Python/PyTest automation frameworks for Databricks ingestion, transformation and curated outputs.
  • Develop source-to-target validation, reconciliation, schema, row-count and business-rule checks.
  • Test APIs, including contract, authentication and negative cases.
  • Integrate automated quality gates into Azure DevOps CI/CD and release processes.
  • Plan regression, integration and performance testing and manage defects through resolution.
  • Validate Power BI/reporting outputs against source data.
  • Create PySpark/Delta Lake test harnesses, fixtures and synthetic or masked data.
  • Document strategy, coverage, runbooks and release-quality results.

What you bring

  • 5+ years of test automation, including 2+ years testing pipelines, ETL/ELT or data platforms.
  • Strong Python and PyTest, including fixtures, parametrization, plugins and reporting.
  • Experience building an automation framework from the ground up.
  • Azure Databricks notebooks, Workflows, Delta Lake and PySpark.
  • Data validation, reconciliation, quality testing and strong SQL.
  • API testing with Postman, Swagger/OpenAPI or Python tooling.
  • Azure DevOps, Git, CI/CD and quality-gate integration.
  • Azure storage/ADLS, Key Vault, Entra ID and Monitor fundamentals.
  • Ability to work onsite in San Diego full time, with clear client-facing communication.

Useful additional experience

  • Great Expectations, Databricks Lakehouse Monitoring or Unity Catalog governance.
  • JMeter, Locust and performance/regression testing.
  • Azure API Management and Power BI validation.
  • AI/ML testing, MLflow or training/inference pipeline tests.
  • Azure Data Factory, Synapse, AKS, Jira/Xray or Azure Test Plans.
  • Relevant ISTQB, Azure data-engineering or Databricks certifications.

Engagement details

  • Long-term engagement.
  • Approximate focus: 70% test automation and data validation; 30% pipeline/platform engineering support.