Apple's App Store is the world's largest and most innovative app marketplace, home to over 1.5 million apps and serving more than half a billion customers every week across all Apple devices. Since the App Store launched in 2008, it has changed how we all live: enabling countless new companies, spawning new industries, and building millions of jobs. We believe we are just getting started.\\n\\nDo you have a strong passion for using data to drive business decisions, generate ideas, and inspire collaborators? As a Software Data Engineer on the App Store Data team, you will play an integral role in helping App Store improve the experience for users and developers every day, through analysis grounded in privacy. We build the solutions, services, and analytics that power data-driven innovation for internal stakeholders and external partners. In a world where apps have become essential to daily life, the App Store team has become essential to Apple's business.
As a member of the App Store Data team, you will play a key role in shaping our strategic direction and driving high-impact initiatives. The data we produce informs Apple Leadership and partners, helping guide decisions on innovation and emerging opportunities. Success in this role requires a strong commitment to building world-class analytical solutions.\n\nYou will build the design and delivery of compliance-critical data products, including pipelines and analytical outputs that meet regulatory and privacy requirements. This role also encompasses analytics engineering, exploratory data analysis, ML-driven data observability and developing scalable self-service data products.
3+ years of experience building production data pipelines on distributed systems \nSolid programming skills in Scala or Java or Python and proficiency in SQL\nHands-on experience in big data technologies, such as: Hadoop, Spark/Flink, Kafka, Airflow, Iceberg, Trino and Kubernetes\nWorking knowledge of data modeling fundamentals, structured and unstructured data analysis, predictive modeling techniques to identify patterns, translating domain requirements into engineering specifications\nActive use of AI coding assistant, actively learning LLM-augmented workflows\nExcellent communication; proven success partnering with cross-functional stakeholders (Product, Engineering, Legal, Privacy etc.)\nBachelor's Degree in Computer Science, Engineering or a Quantitative discipline (e.g., Statistics, Economics, Mathematics).
Exposure to privacy, compliance, or governance data requirements in a pipeline or analytics context\nExposure to ML or statistical anomaly detection, even in a learning or project context\nExperience in writing and maintaining high-quality code using standard methodologies such as code reviews, unit testing, and continuous integration.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: 90733111
- Position Id: 4ef06fdb7d08c885abb493594e583c30
- Posted 7 hours ago
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