Analytics Data Engineer - Siri AI Quality Engineering

The Siri Quality Engineering team is seeking an Analytics Data Engineer to build a Curated, Accurate, Reliable data lake — a governed lakehouse with point-in-time and near-real-time pipelines, and a clear semantic layer — so teams trust and use data to help drive operational and business decisions.

• Build curated, accurate, and reliable data that powers Siri AI
• Design and run our lakehouse so analysts and data scientists can move fast with confidence
• Design and evolve the lakehouse (i.e. Apache Iceberg): schemas, partitioning, compaction, and schema evolution
• Build batch and streaming pipelines with Python/Spark/PySpark; orchestration with Apache Airflow (or similar)
• Ingest from diverse sources; manage metadata, lineage, and the data catalog
• Enforce data quality (tests, SLAs, monitors) and reliability (idempotency, replay, backfills)
• Optimize cost and performance across storage and compute
• Partner with analysts to deliver semantic layers, certified metrics, and feature tables
• Document, review, and automate scripts, runbooks, CI/CD, and infra-as-code

• 5+ years in data engineering
• Expert SQL and Python knowledge
• Deep Spark experience (batch + structured streaming)
• Hands-on experience with a modern data lake technology: Iceberg or equivalent of object storage
• Proven pipeline orchestration (Airflow or equivalent) and Git-based delivery
• Strong data modeling, governance, lineage, and reliability practices

• Comprehensive medical and dental coverage
• Retirement benefits
• Discounted products and free services
• Reimbursement for certain educational expenses
• Discretionary bonuses or commission payments
• Relocation assistance

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