Software Development Test Engineer
Test automation engineer at Amgen ensuring the quality of data pipelines and platforms: designs automated ETL/data validation tests (Python, PySpark, SQL) across AWS and Databricks, integrates tests into CI/CD, and also covers front-end Node.js testing and performance/load testing.
- Compensation
- Not disclosed
- Location
- Hyderabad
- Work setup
- Onsite
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 4+ years
- Category
- Qa
- Posted
Skills
Must have
- Master's degree with 4-6 years in CS/IT or related field, or Bachelor's degree with 6-8 years
- QA experience with strong exposure to data pipeline validation and ETL testing
- Hands-on expertise in front-end Node.js testing and performance testing of infrastructure components
- Validate data accuracy, transformations, schema compliance, and completeness using PySpark and SQL
- Strong hands-on Python (optionally PySpark) for automated data validation scripts
- Proven ETL workflow validation: data transformation logic, schema comparison, source-to-target mapping
- Experience with data integration/processing platforms like Databricks/Snowflake, AWS EMR, Redshift
- Manual and automated testing of both batch and real-time data pipelines
- Performance testing of large-scale data engineering pipelines
- Ability to troubleshoot data issues independently and drive root cause analysis
- Strong understanding of QA methodologies, test planning, test case design, and defect lifecycle management
- API testing using Postman, pytest, or custom automation scripts
- Integrating automated tests into CI/CD pipelines (Selenium, JUnit, Jenkins, GitHub Actions, or similar)
- Knowledge of cloud platforms such as AWS, Azure, GCP
- Excellent critical-thinking, problem-solving, communication, teamwork, and presentation skills
Nice to have
- Certifications in Databricks, AWS, Azure, or data QA (e.g., ISTQB)
- Understanding of data privacy, compliance, and governance frameworks
- Knowledge of UI automated testing frameworks like Selenium, JUnit, TestNG
- Familiarity with monitoring/observability tools such as Datadog, Prometheus, or CloudWatch
- Frameworks like Mocha/Jest and performance testing tools like JMeter or k6
- AWS Certified Data Engineer / Data Analyst (preferred on Databricks or cloud environments)
Full description
ABOUT AMGEN
Amgen harnesses the best of biology and technology to fight the worlds toughest diseases, and make peoples lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond whats known today.
ABOUT THE ROLERole Description:
We are seeking a highly skilled and detail-oriented Data Engineering Test Automation Engineer to ensure the quality, reliability, and performance of our data pipelines and platforms. The ideal candidate has strong experience in data testing, ETL validation, and automation frameworks, and will work closely with data engineers, analysts, and DevOps to build robust test suites. This role involves designing and executing both manual and automated tests for real-time and batch data pipelines across AWS and Databricks platforms, while applying QA best practices in test planning, defect tracking, and lifecycle management to ensure high-quality data delivery. In addition, the resource should have hands-on expertise in front-end Node.js testing and performance testing of infrastructure components, ensuring that user-facing systems are validated for responsiveness, scalability, and reliability. Experience with modern front-end test automation frameworks and load/performance testing tools is highly desirable.
Roles Responsibilities:
- Design, develop, and maintain automated test scripts for data pipelines, ETL jobs, and data integrations.
- Validate data accuracy, completeness, transformations, and integrity across multiple systems.
- Collaborate with data engineers to define test cases and establish data quality metrics.
- Develop reusable test automation frameworks and CI/CD integrations (e.g., Selenium, Jenkins, GitHub Actions).
- Perform performance and load testing for data systems.
- Maintain test data management and data mocking strategies.
- Identify and track data quality issues, ensuring timely resolution.
- Perform root cause analysis and drive corrective actions.
- Contribute to QA ceremonies (standups, planning, retrospectives) and drive continuous improvement in QA processes and culture.
- Build and automate end-to-end data pipeline validations across ingestion, transformation, and consumption layers using Databricks, Apache Spark, and AWS services such as S3, Glue, Athena, and Lake Formation.
Basic Qualifications and Experience:
- Masters degree with 4 - 6 years of experience in Computer Science, IT or related field OR