Sr Associate Test Automation Engineer
Amgen
Sr Associate Test Automation Engineer
Job Description
ABOUT AMGEN
What you will do
- Collaborate with the developers and QAs to design and implement end-to-end test strategies for data validation, CRM (Salesforce/Veeva) layer testing, and Data Migration testing
- Perform manual validation of data pipelines, including source-to-target data mapping, transformation logic, and business rule verification
- Develop and maintain automated data validation scripts using Python and PySpark for both real-time and batch pipelines
- Contribute to the design and enhancement of reusable automation frameworks, with components for schema validation, data reconciliation, and anomaly detection
- Write and manage test plans, test cases, and test data for structured, semi-structured, and unstructured data
- Track, manage, and report defects using tools like JIRA, ensuring thorough root cause analysis and timely resolution
- Collaborate with Data Engineers, Product Managers, and DevOps teams to integrate tests into CI/CD pipelines and enable shift-left testing practices
- Ensure comprehensive test coverage for all aspects of the data lifecycle, including ingestion, transformation, delivery, and consumption
- Participate in QA ceremonies (standups, planning, retrospectives) and continuously contribute to improving the QA process and culture
What we expect of you
- Master’s degree and 3 to 7 years of Computer Science, IT or related field experience OR
- Bachelor’s degree and 5 to 9 years of Computer Science, IT or related field experience OR
- Diploma and 7 to 11 years of Computer Science, IT or related field experience
Must-Have Skills
- Experience in testing automation in front end portals, Mobile iOS applications, .Net Framework and data pipelines
- Practical experience with manual validation of data pipelines and source-to-target testing
- Familiarity with data integration tools and platforms such as Databricks, AWS Glue, Redshift, Veeva/Salesforce
- Strong understanding of test planning, defect tracking, bug lifecycle management, and QA documentation
- Experience working in Agile/Scrum environments with standard QA processes
- Knowledge of test case and defect management tools (e.g., JIRA, TestRail, Zephyr)
- Strong understanding of QA methodologies, test planning, test case design, and defect lifecycle management
- Deep hands-on expertise in SQL, Python, and PySpark for testing and automating validation
- Proven experience in manual and automated testing of batch and real-time data pipelines
- Familiarity with data processing and analytics stacks: Databricks, Spark, AWS (Glue, S3, Athena, Redshift)
- Experience with bug tracking and test management tools like JIRA, TestRail, or Zephyr
- Ability to troubleshoot data issues independently and collaborate with engineering for root cause analysis
- Experience in integrating automated tests into CI/CD pipelines (e.g., Jenkins, GitHub Actions)
- Experience validating data from various file formats such as JSON, CSV, Parquet, and Avro
- Strong ability to validate and automate data quality checks: schema validation, null checks, duplicates, thresholds, and transformation validation
- Hands-on experience with API testing using Postman, pytest, or custom automation scripts
- Experience with testing tools such as Selenium, Copado Robotic Testing, COFTA and other tools
- Strong understanding of data modeling, data warehousing, and data integration concepts
- Knowledge of AnyPoint Platform, Python, Java, Databricks, Salesforce Platform, AWS cloud data platforms
- Proficiency in using AI tools
- Experience building or maintaining test data generators
- Contributions to internal quality dashboards or data observability systems
- Awareness of metadata-driven testing approaches and lineage-based validations
- Experience working with agile Testing methodologies such as Scaled Agile
- Familiarity with automated testing frameworks like Selenium, Copado Robotic Testing, COFTA or PyTest
Locations
- Hyderabad, India
Salary
Salary not disclosed
Estimated Salary Rangehigh confidence
25,000 - 45,000 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 testing automation in front end portals, Mobile iOS applications, .Net Framework and data pipelinesintermediate
- Practical experience with manual validation of data pipelines and source-to-target testingintermediate
- Familiarity with data integration tools and platforms such as Databricks, AWS Glue, Redshift, Veeva/Salesforceintermediate
- Strong understanding of test planning, defect tracking, bug lifecycle management, and QA documentationintermediate
- Experience working in Agile/Scrum environments with standard QA processesintermediate
- Knowledge of test case and defect management tools (e.g., JIRA, TestRail, Zephyr)intermediate
- Strong understanding of QA methodologies, test planning, test case design, and defect lifecycle managementintermediate
- Deep hands-on expertise in SQL, Python, and PySpark for testing and automating validationintermediate
- Proven experience in manual and automated testing of batch and real-time data pipelinesintermediate
- Familiarity with data processing and analytics stacks: Databricks, Spark, AWS (Glue, S3, Athena, Redshift)intermediate
- Experience with bug tracking and test management tools like JIRA, TestRail, or Zephyrintermediate
- Ability to troubleshoot data issues independently and collaborate with engineering for root cause analysisintermediate
- Experience in integrating automated tests into CI/CD pipelines (e.g., Jenkins, GitHub Actions)intermediate
- Experience validating data from various file formats such as JSON, CSV, Parquet, and Avrointermediate
- Strong ability to validate and automate data quality checks: schema validation, null checks, duplicates, thresholds, and transformation validationintermediate
- Hands-on experience with API testing using Postman, pytest, or custom automation scriptsintermediate
- Experience with testing tools such as Selenium, Copado Robotic Testing, COFTA and other toolsintermediate
- Strong understanding of data modeling, data warehousing, and data integration conceptsintermediate
- Knowledge of AnyPoint Platform, Python, Java, Databricks, Salesforce Platform, AWS cloud data platformsintermediate
- Proficiency in using AI toolsintermediate
- Experience building or maintaining test data generatorsintermediate
- Contributions to internal quality dashboards or data observability systemsintermediate
- Awareness of metadata-driven testing approaches and lineage-based validationsintermediate
- Experience working with agile Testing methodologies such as Scaled Agileintermediate
- Familiarity with automated testing frameworks like Selenium, Copado Robotic Testing, COFTA or PyTestintermediate
Required Qualifications
- Master’s degree and 3 to 7 years of Computer Science, IT or related field experience OR (experience)
- Bachelor’s degree and 5 to 9 years of Computer Science, IT or related field experience OR (experience)
- Diploma and 7 to 11 years of Computer Science, IT or related field experience (experience)
Responsibilities
- Collaborate with the developers and QAs to design and implement end-to-end test strategies for data validation, CRM (Salesforce/Veeva) layer testing, and Data Migration testing
- Perform manual validation of data pipelines, including source-to-target data mapping, transformation logic, and business rule verification
- Develop and maintain automated data validation scripts using Python and PySpark for both real-time and batch pipelines
- Contribute to the design and enhancement of reusable automation frameworks, with components for schema validation, data reconciliation, and anomaly detection
- Write and manage test plans, test cases, and test data for structured, semi-structured, and unstructured data
- Track, manage, and report defects using tools like JIRA, ensuring thorough root cause analysis and timely resolution
- Collaborate with Data Engineers, Product Managers, and DevOps teams to integrate tests into CI/CD pipelines and enable shift-left testing practices
- Ensure comprehensive test coverage for all aspects of the data lifecycle, including ingestion, transformation, delivery, and consumption
- Participate in QA ceremonies (standups, planning, retrospectives) and continuously contribute to improving the QA process and culture
Tags & Categories
Sr Associate Test Automation Engineer
Amgen
Sr Associate Test Automation Engineer
Job Description
ABOUT AMGEN
What you will do
- Collaborate with the developers and QAs to design and implement end-to-end test strategies for data validation, CRM (Salesforce/Veeva) layer testing, and Data Migration testing
- Perform manual validation of data pipelines, including source-to-target data mapping, transformation logic, and business rule verification
- Develop and maintain automated data validation scripts using Python and PySpark for both real-time and batch pipelines
- Contribute to the design and enhancement of reusable automation frameworks, with components for schema validation, data reconciliation, and anomaly detection
- Write and manage test plans, test cases, and test data for structured, semi-structured, and unstructured data
- Track, manage, and report defects using tools like JIRA, ensuring thorough root cause analysis and timely resolution
- Collaborate with Data Engineers, Product Managers, and DevOps teams to integrate tests into CI/CD pipelines and enable shift-left testing practices
- Ensure comprehensive test coverage for all aspects of the data lifecycle, including ingestion, transformation, delivery, and consumption
- Participate in QA ceremonies (standups, planning, retrospectives) and continuously contribute to improving the QA process and culture
What we expect of you
- Master’s degree and 3 to 7 years of Computer Science, IT or related field experience OR
- Bachelor’s degree and 5 to 9 years of Computer Science, IT or related field experience OR
- Diploma and 7 to 11 years of Computer Science, IT or related field experience
Must-Have Skills
- Experience in testing automation in front end portals, Mobile iOS applications, .Net Framework and data pipelines
- Practical experience with manual validation of data pipelines and source-to-target testing
- Familiarity with data integration tools and platforms such as Databricks, AWS Glue, Redshift, Veeva/Salesforce
- Strong understanding of test planning, defect tracking, bug lifecycle management, and QA documentation
- Experience working in Agile/Scrum environments with standard QA processes
- Knowledge of test case and defect management tools (e.g., JIRA, TestRail, Zephyr)
- Strong understanding of QA methodologies, test planning, test case design, and defect lifecycle management
- Deep hands-on expertise in SQL, Python, and PySpark for testing and automating validation
- Proven experience in manual and automated testing of batch and real-time data pipelines
- Familiarity with data processing and analytics stacks: Databricks, Spark, AWS (Glue, S3, Athena, Redshift)
- Experience with bug tracking and test management tools like JIRA, TestRail, or Zephyr
- Ability to troubleshoot data issues independently and collaborate with engineering for root cause analysis
- Experience in integrating automated tests into CI/CD pipelines (e.g., Jenkins, GitHub Actions)
- Experience validating data from various file formats such as JSON, CSV, Parquet, and Avro
- Strong ability to validate and automate data quality checks: schema validation, null checks, duplicates, thresholds, and transformation validation
- Hands-on experience with API testing using Postman, pytest, or custom automation scripts
- Experience with testing tools such as Selenium, Copado Robotic Testing, COFTA and other tools
- Strong understanding of data modeling, data warehousing, and data integration concepts
- Knowledge of AnyPoint Platform, Python, Java, Databricks, Salesforce Platform, AWS cloud data platforms
- Proficiency in using AI tools
- Experience building or maintaining test data generators
- Contributions to internal quality dashboards or data observability systems
- Awareness of metadata-driven testing approaches and lineage-based validations
- Experience working with agile Testing methodologies such as Scaled Agile
- Familiarity with automated testing frameworks like Selenium, Copado Robotic Testing, COFTA or PyTest
Locations
- Hyderabad, India
Salary
Salary not disclosed
Estimated Salary Rangehigh confidence
25,000 - 45,000 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 testing automation in front end portals, Mobile iOS applications, .Net Framework and data pipelinesintermediate
- Practical experience with manual validation of data pipelines and source-to-target testingintermediate
- Familiarity with data integration tools and platforms such as Databricks, AWS Glue, Redshift, Veeva/Salesforceintermediate
- Strong understanding of test planning, defect tracking, bug lifecycle management, and QA documentationintermediate
- Experience working in Agile/Scrum environments with standard QA processesintermediate
- Knowledge of test case and defect management tools (e.g., JIRA, TestRail, Zephyr)intermediate
- Strong understanding of QA methodologies, test planning, test case design, and defect lifecycle managementintermediate
- Deep hands-on expertise in SQL, Python, and PySpark for testing and automating validationintermediate
- Proven experience in manual and automated testing of batch and real-time data pipelinesintermediate
- Familiarity with data processing and analytics stacks: Databricks, Spark, AWS (Glue, S3, Athena, Redshift)intermediate
- Experience with bug tracking and test management tools like JIRA, TestRail, or Zephyrintermediate
- Ability to troubleshoot data issues independently and collaborate with engineering for root cause analysisintermediate
- Experience in integrating automated tests into CI/CD pipelines (e.g., Jenkins, GitHub Actions)intermediate
- Experience validating data from various file formats such as JSON, CSV, Parquet, and Avrointermediate
- Strong ability to validate and automate data quality checks: schema validation, null checks, duplicates, thresholds, and transformation validationintermediate
- Hands-on experience with API testing using Postman, pytest, or custom automation scriptsintermediate
- Experience with testing tools such as Selenium, Copado Robotic Testing, COFTA and other toolsintermediate
- Strong understanding of data modeling, data warehousing, and data integration conceptsintermediate
- Knowledge of AnyPoint Platform, Python, Java, Databricks, Salesforce Platform, AWS cloud data platformsintermediate
- Proficiency in using AI toolsintermediate
- Experience building or maintaining test data generatorsintermediate
- Contributions to internal quality dashboards or data observability systemsintermediate
- Awareness of metadata-driven testing approaches and lineage-based validationsintermediate
- Experience working with agile Testing methodologies such as Scaled Agileintermediate
- Familiarity with automated testing frameworks like Selenium, Copado Robotic Testing, COFTA or PyTestintermediate
Required Qualifications
- Master’s degree and 3 to 7 years of Computer Science, IT or related field experience OR (experience)
- Bachelor’s degree and 5 to 9 years of Computer Science, IT or related field experience OR (experience)
- Diploma and 7 to 11 years of Computer Science, IT or related field experience (experience)
Responsibilities
- Collaborate with the developers and QAs to design and implement end-to-end test strategies for data validation, CRM (Salesforce/Veeva) layer testing, and Data Migration testing
- Perform manual validation of data pipelines, including source-to-target data mapping, transformation logic, and business rule verification
- Develop and maintain automated data validation scripts using Python and PySpark for both real-time and batch pipelines
- Contribute to the design and enhancement of reusable automation frameworks, with components for schema validation, data reconciliation, and anomaly detection
- Write and manage test plans, test cases, and test data for structured, semi-structured, and unstructured data
- Track, manage, and report defects using tools like JIRA, ensuring thorough root cause analysis and timely resolution
- Collaborate with Data Engineers, Product Managers, and DevOps teams to integrate tests into CI/CD pipelines and enable shift-left testing practices
- Ensure comprehensive test coverage for all aspects of the data lifecycle, including ingestion, transformation, delivery, and consumption
- Participate in QA ceremonies (standups, planning, retrospectives) and continuously contribute to improving the QA process and culture
Tags & Categories