Software Development Test Engineer

About the role

Amgen is a biotechnology company focused on developing innovative medicines. The Software Development Test Engineer role is a QA position that focuses on data pipeline validation, ETL testing, and performance testing across AWS and Databricks platforms. The engineer will 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, and collaborate with data engineers to define test cases and establish data quality metrics. Responsibilities include developing reusable test automation frameworks and CI/CD integrations (e.g., Selenium, Jenkins, GitHub Actions), performing performance and load testing for data systems, maintaining test data management and mocking strategies, identifying and tracking data quality issues, performing root cause analysis, and contributing to QA ceremonies to drive continuous improvement. The role requires strong experience in QA roles, data pipeline validation, ETL testing, front‑end Node.js testing, performance testing of infrastructure components, and proficiency with PySpark, SQL, Python, Databricks, Snowflake, AWS EMR, Redshift, Postman, pytest, Selenium, JUnit, Jenkins, GitHub Actions, and cloud platforms such as AWS, Azure, and GCP. Preferred qualifications include AWS Certified Data Engineer/Data Analyst, Databricks, AWS, Azure, or ISTQB certifications, and knowledge of data privacy, compliance, governance frameworks, UI automated testing frameworks, monitoring/observability tools, and performance testing tools like JMeter or k6.

What you’ll do

• 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

What you’ll bring

• Master’s degree with 4-6 years in CS/IT or Bachelor’s with 6-8 years in CS/IT
• 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
• Certifications in Databricks, AWS, Azure, or data QA (e.g., ISTQB)

Nice to have

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

Skills

Education

Bachelor's