Software Development Engineer - Test ii
Amgen
Software Development Engineer - Test ii
Job Description
At Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do.
What you will 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., 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
- Develop test automation scripts
- Develop reusable common components for testing
- Develop load and scalability test scripts
- Analyze production issues and develop innovative automation for early detection and prevention of those issues, or for self-healing
What we expect of you
- Master’s degree and 1 to 3 years of computer science and engineering and Test Automation experience
- OR Bachelor’s degree and 3 to 5 years of computer science and engineering and Test Automation experience
- OR Diploma and 7 to 9 years of computer science and engineering and Test Automation experience
Must-Have Skills
- Experience in QA roles, with strong exposure to data pipeline validation and ETL Testing
- Domain Knowledge of R&D domain of life science
- 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 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)
- 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
- Excellent analytical and solving skills
- Strong verbal and written communication skills
- Ability to work effectively with global, virtual teams
- High degree of initiative and self-motivation
- Ability to manage multiple priorities successfully
- Team-oriented, with a focus on achieving team goals
- Ability to learn quickly, be organized and detail oriented
- Strong presentation and public speaking skills
What you can expect of us
- Competitive benefits
- Collaborative culture
- Competitive and comprehensive Total Rewards Plans that are aligned with local industry standards
- Support for professional and personal growth and well-being
Locations
- Hyderabad, India
Salary
Salary not disclosed
Estimated Salary Rangehigh confidence
15,000 - 25,000 USD / yearly
Source: xAI estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Experience in QA roles, with strong exposure to data pipeline validation and ETL Testingintermediate
- Domain Knowledge of R&D domain of life scienceintermediate
- Validate data accuracy, transformations, schema compliance, and completeness across systems using PySpark and SQLintermediate
- Strong hands-on experience with Python, and optionally PySpark, for developing automated data validation scriptsintermediate
- Proven experience in validating ETL workflows, with a solid understanding of data transformation logic, schema comparison, and source-to-target mappingintermediate
- Experience working with data integration and processing platforms like Databricks/Snowflake, AWS EMR, Redshift etc.intermediate
- Experience in manual and automated testing of data pipelines executions for both batch and real-time data pipelinesintermediate
- Perform performance testing of large-scale complex data engineering pipelinesintermediate
- Ability to troubleshoot data issues independently and collaborate with engineering teams for root cause analysisintermediate
- Strong understanding of QA methodologies, test planning, test case design, and defect lifecycle managementintermediate
- Hands-on experience with API testing using Postman, pytest, or custom automation scriptsintermediate
- Experience integrating automated tests into CI/CD pipelines using tools like Jenkins, GitHub Actions, or similarintermediate
- Knowledge of cloud platforms such as AWS, Azure, GCPintermediate
- Certifications in Databricks, AWS, Azure, or data QA (e.g., ISTQB)intermediate
- Understanding of data privacy, compliance, and governance frameworksintermediate
- Knowledge of UI automated testing frameworks like Selenium, JUnit, TestNGintermediate
- Familiarity with monitoring/observability tools such as Datadog, Prometheus, or Cloud Watchintermediate
- Excellent analytical and solving skillsintermediate
- Strong verbal and written communication skillsintermediate
- Ability to work effectively with global, virtual teamsintermediate
- High degree of initiative and self-motivationintermediate
- Ability to manage multiple priorities successfullyintermediate
- Team-oriented, with a focus on achieving team goalsintermediate
- Ability to learn quickly, be organized and detail orientedintermediate
- Strong presentation and public speaking skillsintermediate
Required Qualifications
- Master’s degree and 1 to 3 years of computer science and engineering and Test Automation experience (experience)
- OR Bachelor’s degree and 3 to 5 years of computer science and engineering and Test Automation experience (experience)
- OR Diploma and 7 to 9 years of computer science and engineering and Test Automation experience (experience)
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., 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
- Develop test automation scripts
- Develop reusable common components for testing
- Develop load and scalability test scripts
- Analyze production issues and develop innovative automation for early detection and prevention of those issues, or for self-healing
Benefits
- general: Competitive benefits
- general: Collaborative culture
- general: Competitive and comprehensive Total Rewards Plans that are aligned with local industry standards
- general: Support for professional and personal growth and well-being
Tags & Categories
Software Development Engineer - Test ii
Amgen
Software Development Engineer - Test ii
Job Description
At Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do.
What you will 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., 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
- Develop test automation scripts
- Develop reusable common components for testing
- Develop load and scalability test scripts
- Analyze production issues and develop innovative automation for early detection and prevention of those issues, or for self-healing
What we expect of you
- Master’s degree and 1 to 3 years of computer science and engineering and Test Automation experience
- OR Bachelor’s degree and 3 to 5 years of computer science and engineering and Test Automation experience
- OR Diploma and 7 to 9 years of computer science and engineering and Test Automation experience
Must-Have Skills
- Experience in QA roles, with strong exposure to data pipeline validation and ETL Testing
- Domain Knowledge of R&D domain of life science
- 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 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)
- 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
- Excellent analytical and solving skills
- Strong verbal and written communication skills
- Ability to work effectively with global, virtual teams
- High degree of initiative and self-motivation
- Ability to manage multiple priorities successfully
- Team-oriented, with a focus on achieving team goals
- Ability to learn quickly, be organized and detail oriented
- Strong presentation and public speaking skills
What you can expect of us
- Competitive benefits
- Collaborative culture
- Competitive and comprehensive Total Rewards Plans that are aligned with local industry standards
- Support for professional and personal growth and well-being
Locations
- Hyderabad, India
Salary
Salary not disclosed
Estimated Salary Rangehigh confidence
15,000 - 25,000 USD / yearly
Source: xAI estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Experience in QA roles, with strong exposure to data pipeline validation and ETL Testingintermediate
- Domain Knowledge of R&D domain of life scienceintermediate
- Validate data accuracy, transformations, schema compliance, and completeness across systems using PySpark and SQLintermediate
- Strong hands-on experience with Python, and optionally PySpark, for developing automated data validation scriptsintermediate
- Proven experience in validating ETL workflows, with a solid understanding of data transformation logic, schema comparison, and source-to-target mappingintermediate
- Experience working with data integration and processing platforms like Databricks/Snowflake, AWS EMR, Redshift etc.intermediate
- Experience in manual and automated testing of data pipelines executions for both batch and real-time data pipelinesintermediate
- Perform performance testing of large-scale complex data engineering pipelinesintermediate
- Ability to troubleshoot data issues independently and collaborate with engineering teams for root cause analysisintermediate
- Strong understanding of QA methodologies, test planning, test case design, and defect lifecycle managementintermediate
- Hands-on experience with API testing using Postman, pytest, or custom automation scriptsintermediate
- Experience integrating automated tests into CI/CD pipelines using tools like Jenkins, GitHub Actions, or similarintermediate
- Knowledge of cloud platforms such as AWS, Azure, GCPintermediate
- Certifications in Databricks, AWS, Azure, or data QA (e.g., ISTQB)intermediate
- Understanding of data privacy, compliance, and governance frameworksintermediate
- Knowledge of UI automated testing frameworks like Selenium, JUnit, TestNGintermediate
- Familiarity with monitoring/observability tools such as Datadog, Prometheus, or Cloud Watchintermediate
- Excellent analytical and solving skillsintermediate
- Strong verbal and written communication skillsintermediate
- Ability to work effectively with global, virtual teamsintermediate
- High degree of initiative and self-motivationintermediate
- Ability to manage multiple priorities successfullyintermediate
- Team-oriented, with a focus on achieving team goalsintermediate
- Ability to learn quickly, be organized and detail orientedintermediate
- Strong presentation and public speaking skillsintermediate
Required Qualifications
- Master’s degree and 1 to 3 years of computer science and engineering and Test Automation experience (experience)
- OR Bachelor’s degree and 3 to 5 years of computer science and engineering and Test Automation experience (experience)
- OR Diploma and 7 to 9 years of computer science and engineering and Test Automation experience (experience)
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., 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
- Develop test automation scripts
- Develop reusable common components for testing
- Develop load and scalability test scripts
- Analyze production issues and develop innovative automation for early detection and prevention of those issues, or for self-healing
Benefits
- general: Competitive benefits
- general: Collaborative culture
- general: Competitive and comprehensive Total Rewards Plans that are aligned with local industry standards
- general: Support for professional and personal growth and well-being
Tags & Categories