Data Product Engineering Lead - Wallet, Payments & Commerce

Apple Apple · Big Tech · Austin, TX +1 · Software and Services

Seeking a Data Product Engineering Lead to build and maintain scalable analytical data products and architectures for Apple's Payments & Commerce business. This role involves instrumenting APIs, designing data/ML pipelines, optimizing workflows, and collaborating with partners to deliver actionable insights and decision tools. Requires strong SQL, Scala/Python/Java, data pipeline tools (Spark, Kafka, Airflow), cloud platforms, data warehousing, and data modeling.

What you'd actually do

  1. Instrument APIs, user journey and interaction flows to systematically collect behavioral, transactional, and operational data, enabling robust analytics and insightful reporting
  2. Design, develop, and maintain scalable analytical data products and architectures for Payments & Commerce products.
  3. 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
  4. Optimize data workflows and pipelines to enhance data processing efficiency and reliability.
  5. Collaborate closely with diverse set of partners to gather requirements, prioritize use cases, and ensure high-quality data products delivery.

Skills

Required

  • SQL
  • Scala
  • Python
  • Java
  • Apache Spark
  • Kafka
  • Airflow
  • CI/CD practices
  • version control
  • AWS
  • Azure
  • GCP
  • Snowflake
  • Databricks
  • Tableau
  • data warehousing
  • data modeling
  • metric standardization
  • problem-solving
  • analytical skills
  • communication skills
  • social skills
  • presentation skills
  • attention to detail
  • time management
  • handling tight deadlines

Nice to have

  • Apache Spark
  • Kafka
  • Airflow
  • Trino
  • OLAP
  • NRT
  • data mesh architectures
  • Generative AI/LLM applications
  • data quality frameworks
  • validation
  • profiling
  • anomaly detection
  • synthetic data generation

What the JD emphasized

  • 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

Other signals

  • data pipelines
  • ML pipelines
  • analytical data products
  • data modeling
  • metrics foundation