Description
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 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
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