Databricks QA Automation Engineer - Data Quality Champion

Vizient; Chicago (IL); On-site; USD 89,000 - 156,000; Full time

Job summary

Vizient is seeking a data test automation professional to design and maintain automated test suites for Databricks jobs, Delta tables, and ETL pipelines. You will validate complex data transformations, perform reconciliations, and ensure data quality across systems in a large-scale environment.

You will also build test data, reusable utilities, and CI/CD integrations, and collaborate with data engineering to resolve issues while enhancing test frameworks and coverage.

Responsibilities

• Develop and maintain automated test suites for Databricks jobs, Delta tables, views, data transformations, and ETL pipelines.
• Validate metric calculations, business rules, aggregations, derived values, and source-to-target data transformations within Databricks.
• Perform source-to-target reconciliation and validate data completeness, accuracy, consistency, timeliness, and referential integrity across systems.
• Develop automated tests for full and incremental loads, updates, deletes, retries, exception handling, and recovery scenarios.
• Create test data, SQL validation queries, reusable utilities, and reconciliation frameworks to improve testing efficiency and coverage.
• Integrate automated data tests into CI/CD pipelines and enhance test automation frameworks and processes.
• Perform functional, integration, regression, and end-to-end testing across large-scale data solutions.
• Analyze test failures, conduct root cause analysis, document defects, and collaborate with data engineering and platform teams to resolve issues.

Job description

Vizient is seeking a data test automation professional to design and maintain automated test suites for Databricks jobs, Delta tables, and ETL pipelines. You will validate complex data transformations, perform reconciliations, and ensure data quality across systems in a large-scale environment.

You will also build test data, reusable utilities, and CI/CD integrations, and collaborate with data engineering to resolve issues while enhancing test frameworks and coverage.