Lead AQA Data Engineer

Job Description

Test automation is an area to improve: the process and framework need to be enhanced, while high data volumes in pipelines and ETL/ETF process verification are not automated today. GenAI is being experimented with but is not yet mature.

Requirements

• Proven experience in QA, testing web applications, data pipelines, and large-scale cloud-based services.
• Expertise in test planning, creating test cases, and executing manual and automated tests collaboratively with engineering and product stakeholders.
• Experience building automated test frameworks from scratch or significantly expanding existing ones.
• Technology stack: Ember.js, React.js, TypeScript, Django, Ruby on Rails, FastAPI, Airflow, Apache Spark, AWS Aurora Postgres, Cassandra, Trino, Apache Iceberg, AWS SQS, Docker, and test case management tools such as JAMA or Radar.
• Strong analytical and problem-solving skills with attention to system-wide complexities.
• Experience with Agile, CI/CD pipelines, and Git.
• Experience with data pipelines is required.

Scope

1. Manual Testing: Validate developer fixes and new features against collaboratively defined test cases.
2. Automated Testing: Automate test cases in close collaboration with manual testers before features are released to production. Tests that cannot be automated must be documented and tracked as recurring manual regression items.
3. Performance Testing: Build and maintain a framework to track system performance and validate functional and non-functional requirements.
4. Load Testing: Build and maintain a framework to evaluate load-bearing capacity.

The QA lead will be the point of contact with Apple teams and manage the work for QA engineers. The role requires lead-level automation expertise, combining archival knowledge with hands-on work to improve the current QA solution and approach.

Deliverables

• Completed test plans, cases, and scripts for the Recon data pipeline.
• An automated test suite covering UI, API, backend services, and data pipeline correctness.
• A QA-owned regression pipeline for pre-release runs.
• Regular test reports documenting results, defects, and recommendations.
• Weekly written progress reports covering workload management, blockers, automation coverage trends, and upcoming priorities.