In this role, you will drive quality for large-scale distributed data systems that power App Store analytics. You will collaborate closely with engineering, data, and program management teams to define test strategies, contribute to automation frameworks, and ensure high data fidelity across ingestion, transformation, and reporting layers. You will be responsible for:
*Implementing and maintaining automated validation frameworks for data pipelines and services
*Integrating automated tests into CI/CD pipelines to ensure continuous feedback and early defect detection
*Partnering with developers to shift quality left by embedding testability into data workflows and APIs
*Ensuring consistency and correctness of client-to-backend data flows across iOS, macOS, tvOS, and Web

This role requires a self-driven engineer with strong technical depth, solid analytical skills, and the ability to influence quality across complex, evolving systems.

Minimum Qualifications
Bachelor’s degree in Computer Science, Engineering, or similar field
At least 7+ years industry experience in a similar role
Strong proficiency in Python and/or Java for backend test automation and data validation
Working knowledge of SQL and large-scale dataset validation across distributed storage or data lake environments
Experience with REST API testing and automation
Experience with CI/CD pipelines and continuous testing frameworks
Proven experience implementing Shift-Left testing practices and embedding automation early in the SDLC
Strong analytical, debugging, and communication skills

Preferred Qualifications
Hands-on experience with Big Data frameworks (Spark, Kafka, Flink, Hadoop, Hive, Iceberg)
Familiarity with containerized environments (Docker, Kubernetes) and deployment automation
Knowledge of Charles Proxy, Postman, or equivalent tools for API and network validation
Exposure to iOS/macOS platforms and Swift (for end-to-end validation scenarios)
Passion for building maintainable, reusable, and scalable test automation systems