Senior Test Automation Engineer - Data Pipelines

About the role

Amgen is looking for a hands-on Senior QA & Test Automation Specialist (Test Automation Engineer) with strong experience in data validation, ETL testing, test automation and QA process ownership. You will design and run manual and automated test strategies for complex real-time and batch data pipelines, help build automation frameworks and ensure high-quality data delivery across AWS and Databricks-based analytics platforms.

Key responsibilities

• Design and implement end-to-end test strategies for data validation, semantic layer testing and GraphQL API validation with the QA Manager.
• Manually validate data pipelines, including source-to-target mapping, transformation logic and business rules.
• Build and maintain automated data validation scripts in Python and PySpark for real-time and batch pipelines.
• Help design reusable automation frameworks with schema validation, data reconciliation and anomaly detection.
• Validate semantic layers (e.g. Looker, dbt) and GraphQL APIs for consistency and contract compliance.
• Write test plans, test cases and test data, and track defects in JIRA with root cause analysis.
• Integrate tests into CI/CD pipelines with Data Engineers, Product Managers and DevOps, and take part in QA ceremonies.

Required profile

• 6-9 years in QA roles, with at least 3+ years in data pipeline testing and ETL validation.
• Experience with manual validation of data pipelines and source-to-target testing.
• Validating GraphQL APIs, semantic layers and schema/data contract compliance.
• Agile/Scrum experience and familiarity with Selenium, JUnit, TestNG or PyTest.
• Bachelor's or Master's degree in computer science and engineering preferred.

Required skills

• SQL, Python and PySpark; knowledge of Databricks, AWS Glue, Redshift, Athena or BigQuery.
• Test management tools such as JIRA, TestRail or Zephyr.
• CI/CD integration (e.g. Jenkins, GitHub Actions) and API testing with Postman or pytest.
• Data formats: JSON, CSV, Parquet, Avro.
• Good to have: data governance tools (Apache Atlas, Collibra, Alation) and observability tools (Datadog, Prometheus, CloudWatch).