Sr Associate Test Automation Engineer

Career Category

Information Systems

Job Description

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, hands-on Senior Associate QA Automation Engineer with strong expertise in test automation, Veeva CRM application testing, mobile/iPad testing, API and integration testing, data validation, and AI-enabled quality engineering.

The role will be responsible for designing, developing, and executing scalable automation solutions across complex enterprise applications, CRM platforms, mobile applications, APIs, integrations, and data pipelines.

The successful candidate will play a key role in increasing automation coverage, reducing manual regression effort, accelerating release validation, and improving overall product quality. The engineer will also leverage AI-assisted testing capabilities to improve test design, automation development, test-data generation, defect analysis, and QA productivity.

This role requires strong hands-on technical capability along with ownership of QA processes including test strategy, test planning, automation framework development, defect management, regression testing, and continuous quality improvement.

ROLES & RESPONSIBILITIES

Collaborate with Developers, QA, Product, Data Engineering, DevOps, and business stakeholders to define and implement end-to-end test strategies, test plans, test cases, test data, traceability, regression planning, release validation, and quality improvements across CRM Salesforce/Veeva, mobile/iPad, API, integration, data validation, and data migration scenarios.

Perform manual and automated validation of data pipelines across structured, semi-structured, and unstructured data, including source-to-target mapping, transformation logic, business-rule verification, schema checks, record-count reconciliation, null/duplicate checks, referential integrity, thresholds, anomaly detection, ingestion, transformation, delivery, consumption, and migration-quality validation.

Design, develop, maintain, and execute reusable automation frameworks, automated regression suites, and data-validation scripts using tools and technologies such as Selenium, Copado Robotic Testing, COFTA, Microsoft Playwright, PyTest, Postman/Newman, Python, PySpark, and equivalent frameworks for CRM, web, mobile/iPad, API, integration, batch, real-time, and data testing.

Build and enhance reusable automation components for schema validation, data reconciliation, anomaly detection, lineage-based validation, metadata/configuration-driven testing, test-data generation, mocks, stubs, automation utilities, and migration-quality checks.

Automate API and integration testing across middleware, CRM, cloud platforms, data platforms, and upstream/downstream systems, covering request/response validation, authentication, payloads, business rules, error handling, negative scenarios, retries, and batch or real-time integration failures.

Integrate automated tests into CI/CD pipelines, support automated quality gates, enable shift-left testing, and improve release readiness through smoke, sanity, functional, API, mobile, integration, data, and regression validation.

Track, manage, and report defects using JIRA and related tools, ensuring clear documentation, root-cause analysis, timely resolution, retesting, quality reporting, QA metrics, internal dashboards, and continuous improvement of QA processes and culture across Agile/SAFe delivery cycles.

Leverage Generative AI and AI-assisted engineering tools responsibly to accelerate test-case creation, automation development, code review, test-data generation, defect triage, log analysis, documentation, coverage-gap identification, and automation-maintenance insights while ensuring AI-generated artifacts and engineering outputs are reviewed, traceable, secure, compliant, and aligned with enterprise quality, privacy, governance, and responsible-use expectations.

BASIC QUALIFICATIONS & EXPERIENCE

Master’s degree in Computer Science, Information Technology, Engineering or related discipline with 1–3 years of relevant experience, OR

Bachelor’s degree with 3–5 years of relevant experience, OR

Diploma with 7–9 years of relevant experience.

Relevant experience should include hands-on QA automation across enterprise applications, CRM, APIs, integrations, mobile applications and/or data platforms.

FUNCTIONAL / TECHNICAL SKILLS

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

AI-enabled quality engineering: Practical experience using Generative AI or AI-assisted development/testing tools for test generation, automation development, test-data generation, defect analysis, documentation, prompt refinement, and validation of AI-generated outputs.

Responsible AI use: Awareness of enterprise AI security, privacy, governance, and responsible-use considerations when applying AI to QA and software engineering activities.

 

GOOD-TO-HAVE SKILLS

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, Veeva/Salesforce Platform, AWS cloud data platforms

Experience evaluating or implementing AI-powered testing/automation solutions

Experience with large-scale application or data migration testing.

Experience developing QA dashboards and quality engineering metrics.

Experience creating reusable test-data generators, mocks, stubs, and automation utilities.

PROFESSIONAL CERTIFICATIONS

Preferred:

Salesforce/Veeva CRM platform certification

AWS Associate/Professional certification

 

SOFT SKILLS

Excellent analytical, critical-thinking, and problem-solving skills.

Strong automation-first and continuous-improvement mindset.

Ability to understand complex business processes and translate them into effective automated test scenarios.

Strong ownership and accountability for quality across the delivery lifecycle.

Strong written and verbal communication skills.

Curiosity and willingness to evaluate emerging technologies, particularly AI and intelligent automation, and translate them into practical improvements in software quality.

EQUAL OPPORTUNITY STATEMENT

Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status.

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 accommodation.

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