Tools & Automation Backend Quality Engineer – App Store Analytics

Apple•Seattle, WA

About The Position

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. The engineer will drive quality for large-scale distributed data systems, covering the data lifecycle from client instrumentation through backend aggregation and reporting dashboards. The role applies shift-left testing principles and integrates test automation into CI/CD pipelines. The engineer will collaborate with engineering, data, and program management teams to define test strategies, develop test automation, and ensure data quality across ingestion, transformation, reporting, backend, frontend, and UI layers. Responsibilities include building scalable validation frameworks and utilities, validating distributed data pipelines, investigating data issues, and documenting testing approaches and results. The role also uses GenAI to improve testing efficiency and effectiveness.

Requirements

Bachelor’s degree in Computer Science, Engineering, or a similar field.
At least 7 years of industry experience in a similar role.
Strong proficiency in Python and/or Java for backend, frontend, and data pipeline test automation.
Working knowledge of SQL and large-scale dataset validation across distributed storage or data lake environments.
Experience with REST API testing and test automation.
Experience with UI testing and test 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.
Hands-on experience with Big Data frameworks including Spark, Kafka, Flink, Hadoop, Hive, and Iceberg.
Hands-on experience with mobile testing.
Passion for building maintainable, reusable, and scalable test automation systems.

Nice To Haves

Familiarity with containerized environments such as Docker and 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.

Responsibilities

Implement and maintain automated validation frameworks for data pipelines, backend services, and frontend services.
Integrate automated tests into CI/CD pipelines to provide continuous validation, early defect detection, and continuous deployment.
Partner with developers to embed testability into data workflows, APIs, and UI dashboards early in the development lifecycle.
Ensure consistency and correctness of client-to-backend data flows across iOS, macOS, tvOS, visionOS, and Web.
Validate Spark, Kafka, Flink, Hive, Hadoop, and Iceberg data pipelines for correctness, completeness, and performance.
Develop scalable utilities for schema validation, data comparison, and regression checks across distributed datasets.
Conduct functional, regression, and data integrity testing across storage and compute layers.
Build monitoring and alerting mechanisms for pipeline health and data quality KPIs.
Investigate, isolate, and debug complex data issues across client, backend, and frontend layers.
Design and document test strategies, automation architecture, and validation reports.
Collaborate with data, backend, and frontend engineers to drive shift-left quality practices.
Leverage GenAI to improve testing efficiency and effectiveness.