Lead AQA Data Engineer

Job Description

Must have: Test automation is an area to improve, process, framework need to be enhanced, the volume of data is high on the pipelines and ETL/ETF process verification is not automated today. GenAI is in experiment but not 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, developed collaboratively with engineering and product stakeholders.

• Demonstrated track record of building automated test frameworks from scratch or significantly expanding existing ones.

Technology stack:

▪ Frontend: Ember.js, React.js, TypeScript

▪ Backend: Django, Ruby on Rails, FastAPI, Airflow, Apache Spark

▪ Data: AWS Aurora Postgres, Cassandra, Trino, Apache Iceberg, AWS SQS

▪ Tools: Docker

• QA tooling (open to vendor proposals that best align with our setup)

• A test case management tool such as JAMA or Radar

• Strong analytical and problem-solving skills with attention to system-wide complexities.

• Experience with Agile, CI/CD pipelines, and version control (Git).

Note: No perfect match needed, but the work with data pipelines is a must

Scope:

1. Manual Testing - Validate developer fixes and new features as they are completed, hands-on, case-by-case testing against documented test cases that have been collaboratively defined with engineers and product owners ahead of time.

2. Automated Testing - QA is expected to automate test cases in close collaboration with manual testers, with automation completed before features ship to production. Automated tests should be added to the test suite as a condition of release.If a test case cannot be automated, it must be explicitly documented and tracked as a recurring manual regression item so nothing is silently dropped.

Nice to have

Performance Testing - Build and maintain a framework to track Recon's system performance over time, validating both functional andnon-functional requirements. While critical during database upgrades, infrastructure changes, and majorreleases, performance testing should also be integrated into the regular release cycle to catch holistic, cross-component regressions that fall outside individual developer scope.

Load Testing - Build and maintain a framework to evaluate Recon's load-bearing capacity. Like performance testing, this is run infrequently but is essential when needed.

Key points: Test automation is an area to improve, process, framework need to be enhanced, the volume of data is high on the pipelines and ETL/ETF process verification is not automated today.GenAI is in experiment but not mature. The QA lead will be the point of contact with Apple teams and manage the work for QA engineers, is expected from the lead automation expertise (Archive + hands on) to improve current solution and approach for QA.

Deliverables

Completed test plans, cases, and scripts for the Recon data pipeline, developed in collaboration with engineering and product owners.

Automated test suite covering UI, API, backend services, and data pipeline correctness, with measurable, growing coverage over the year.

A QA-owned regression pipeline for pre-release runs. (Longer-term goal: integration into Recon CI/CD pipelines once automation coverage is mature.)

Regular test reports documenting results, defects, and recommendations.

Weekly written progress reports covering workload management, blockers, automation coverage trend, and upcoming priorities.