Data Product Engineering Lead - Wallet, Payments & Commerce
Apple
Product
Austin, TX, USA
Posted on Mar 31, 2026
We are seeking pragmatic Data Product Engineering Lead to join a team passionate about creating analytic experiences that simplify data into insights and catalyze decision making. The WPC Data Science and Analytics Engineering team collaborates with a wide variety of partners within Apple to optimize user experience and systems efficiency across Apple Services Payments & Commerce lines of business.
The job is cross-functional and requires making sense of Internet-scale data across numerous product, engineering and customer touch points. It requires fluency using statistics, data modeling and modern interactive visualizations to answer specific questions, design thinking about personas and data schemas, data and ml pipelines, data visualization skills, and most importantly, a passion for creating scalable analytics strategies to communicate actionable insights and intuitive decision tools to all levels of the company.
- In this role, you will:
- Instrument APIs, user journey and interaction flows to systematically collect behavioral, transactional, and operational data, enabling robust analytics and insightful reporting
- Design, develop, and maintain scalable analytical data products and architectures for Payments & Commerce products.
- You will help design and build solid metric foundation layer that will be fundamental to drive trustable insights and machine learning predictive/forecasting and AI driven inferences
- Optimize data workflows and pipelines to enhance data processing efficiency and reliability.
- Collaborate closely with diverse set of partners to gather requirements, prioritize use cases, and ensure high-quality data products delivery.
- Bachelor’s or Master’s degree in Computer Science or a related technical field or equivalent experience
- 8+ years of experience in designing, developing and deploying next-gen Analytical Data Products leveraging data with Data Visualizations, ML & AI pipelines preferably for a digital subscription business
- Strong proficiency in SQL, Scala, Python, or Java, with hands-on experience in data pipeline tools (e.g., Apache Spark, Kafka, Airflow), CI/CD practices, and version control.
- Proficiency with cloud platforms (AWS, Azure, GCP) and data management and analytics tools like Snowflake, Databricks and Tableau or other visualization tools.
- Strong understanding of data warehousing, data modeling (dimensional/star schemas), and metric standardization.
- Excellent problem-solving and analytical skills, with the ability to influence stakeholders and drive adoption of best practices.
- Experience leading discovery workshops with domain experts and synthesizing requirements into wireframes, mockups and development specifications.
- You have good communication, social and presentation skills with meticulous attention to detail.
- Strong time management skills with the ability to handle work to tight deadlines and the pressure of executive requests over multiple projects.
- Experience authoring technical and instrumentation specs, and working with APIs and message schemas (MSDs).
- Proven ability to design reusable frameworks, tools, and automation to accelerate platform adoption.
- Hands-on experience with distributed querying (Trino), real-time analytics (OLAP), near-real-time processing (NRT), and data mesh architectures.
- Familiarity with Generative AI/LLM applications for test generation, anomaly detection, documentation automation, and privacy-safe synthetic data creation.
- Proven experience building data quality frameworks (validation, profiling, anomaly detection, synthetic data generation).
- Track record of independent problem-solving, sound technical judgment, and delivering impactful results at scale.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.