Tools & Automation Backend Quality Engineer – App Store Analytics

The App Store Analytics Quality Engineering team ensures the accuracy reliability and integrity of customer experience data that powers features and insights across the App Store ecosystem. We are seeking a Backend Test Engineer with strong experience in Big Data environments (Spark Kafka Flink Hadoop Hive Iceberg) and the ability to build scalable robust backend test automation using Java or Python. nnThis role is central to ensuring quality throughout the data lifecycle from client instrumentation to backend aggregation and reporting by applying shift-left testing principles embedding quality checks early in development and integrating test automation within CI/CD pipelines.

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: n*Implementing and maintaining automated validation frameworks for data pipelines and services n*Integrating automated tests into CI/CD pipelines to ensure continuous feedback and early defect detection n*Partnering with developers to shift quality left by embedding testability into data workflows and APIs n*Ensuring consistency and correctness of client-to-backend data flows across iOS macOS tvOS and Web nnThis role requires a self-driven engineer with strong technical depth solid analytical skills and the ability to influence quality across complex evolving systems.

Design implement and maintain automated test frameworks for backend data validation ETL verification and system integration testingnCollaborate with data and backend engineers to embed test hooks and validations early in the development lifecycle (Shift-Left)nIntegrate automated tests into CI/CD pipelines to ensure continuous quality validationnValidate data pipelines built on Spark Kafka Flink Hive Hadoop and Iceberg ensuring correctness completeness and performancenDevelop scalable utilities for schema validation data comparison and regression checks across distributed datasetsnConduct functional regression and data integrity testing across multiple storage and compute layersnBuild monitoring and alerting mechanisms for pipeline health and data quality KPIsnInvestigate isolate and debug complex data issues across client and backend layersnDocument test strategies automation architecture and validation reports

Bachelors degree in Computer Science Engineering or similar fieldnAt least 7 years industry experience in a similar rolenStrong proficiency in Python and/or Java for backend test automation and data validationnWorking knowledge of SQL and large-scale dataset validation across distributed storage or data lake environmentsnExperience with REST API testing and automationnExperience with CI/CD pipelines and continuous testing frameworksnProven experience implementing Shift-Left testing practices and embedding automation early in the SDLCnStrong analytical debugging and communication skills

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