Software Development Test Engineer

ABOUT AMGEN

Amgen harnesses the best of biology and technology to fight the world s toughest diseases, and make people s 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 what s known today.

ABOUT THE ROLE

Role 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:

• Master s degree with 4 - 6 years of experience in Computer Science, IT or related field OR

• Bachelor s degree with 6 - 8 years of experience in Computer Science, IT or related field

Functional Skills:

Must-Have Skills:

• Experience in QA roles, 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 across systems using PySpark and SQL.

• Strong hands-on experience with Python, and optionally PySpark, for developing automated data validation scripts.

• Proven experience in validating ETL workflows, with a solid understanding of data transformation logic, schema comparison, and source-to-target mapping.

• Experience working with data integration and processing platforms like Databricks/Snowflake, AWS EMR, Redshift etc

• Experience in manual and automated testing of data pipelines executions for both batch and real-time data pipelines.

• Perform performance testing of large-scale complex data engineering pipelines.

• Ability to troubleshoot data issues independently and collaborate with engineering teams for root cause analysis

• Strong understanding of QA methodologies, test planning, test case design, and defect lifecycle management.

• Hands-on experience with API testing using Postman, pytest, or custom automation scripts

• Experience integrating automated tests into CI/CD pipelines using tools like Selenium, JUnit, Jenkins, GitHub Actions, or similar.

• Knowledge of cloud platforms such as AWS, Azure, GCP.

Good-to-Have Skills:

• 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 Cloud Watch

• Frameworks like Mocha/Jest and performance testing tools like JMeter or k6

Professional Certifications (Preferred):

• AWS Certified Data Engineer / Data Analyst (preferred on Databricks or cloud environments)

Soft Skills:

• Excellent critical-thinking and problem-solving skills

• Strong communication and collaboration skills

• Demonstrated awareness of how to function in a team setting

• Demonstrated presentation skills

EQUAL OPPORTUNITY STATEMENT

We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.