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Senior Data Engineer

Apple· Operations and Supply Chain
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SingaporeFull-timePosted 1mo ago

About the role

Senior Data Engineer to design, build, and maintain end-to-end data pipelines and operational software applications for Apple's Pacific Operations within Worldwide Sales & Operations Support. Focus on bridging complex data ecosystems, delivering decision-making tools, and enabling AI/agentic solutions while ensuring operational rigor and observability.

Responsibilities

  • Design robust ingestion and transformation pipelines
  • Build polyglot storage strategies (relational, vector, and graph), and build the downstream backend services, APIs, and user interfaces that turn data into operational tools.
  • Build and maintain scalable batch and streaming data pipelines across diverse storage paradigms, including relational warehouses, vector stores for semantic search, and graph databases for multi-hop network and entity modeling.
  • Work with data science and analytics teams to develop production-ready backend services and lightweight functional interfaces that operationalize clean data for decision-making and automation.
  • Serve data to users through agentic solutions — building the retrieval, tools, and interfaces that let AI agents answer questions and take action on our data.
  • Apply systems thinking to diagnose complex, multi-variable business problems, map feedback loops and bottlenecks, and design resilient architectures with attention to latency and dependencies.
  • Evaluate technology trade-offs, implementing deterministic rules engines, constraint optimization, or statistical models, and integrate applied AI/LLMs where leverage is clear.
  • Ensure operational rigor and observability through data contracts, automated integration tests, CI/CD pipelines, and monitoring for silent pipeline failures, index drift, and model latency.

Qualifications

  • 7+ years of practical experience building production data pipelines, distributed systems, and backend services.
  • Deep proficiency in Python, modern SQL, and data modeling frameworks (e.g., dbt).
  • Hands-on experience with orchestration tooling (e.g., Airflow, Dagster, Prefect) and modern data warehouses (e.g., PostgreSQL, Snowflake, DuckDB).
  • Experience applying vector databases/extensions (e.g., Milvus, pgvector, Qdrant, Pinecone) for embedding, semantic search, hybrid search, and RAG retrieval.
  • Experience applying graph databases (e.g., TigerGraph, Neo4j, Memgraph, AWS Neptune) for data modeling, queries (Cypher/Gremlin), and multi-hop traversals.
  • Strong API development experience using modern frameworks (e.g., FastAPI, Go, Node.js) and async queues/streams (e.g., Celery, Redis, Kafka).
  • Working knowledge of AI agents operation — tool calling, retrieval, context management, multi-step reasoning — and delivering data through agentic solutions.
  • Practical exposure to applied AI/ML workflows (embeddings, semantic caching, model serving endpoints, or RAG pipelines).
  • Strong systems-thinking abilities to identify second-order effects and constraints.
  • Ability to operate autonomously across the stack to diagnose operational problems and deliver solutions.
  • Track record of owning systems end-to-end and setting technical standards or direction for a team.
  • Bachelor’s degree in Computer Science, Data Engineering, or related field.

Skills

Required:PythonSQL & Data Modeling (dbt)Orchestration ToolsData Warehouses & StorageVector Databases / EmbeddingsGraph Databases & QueriesAPI Development
Nice to have:AI Agents & LLM ToolingApplied AI/ML WorkflowsObservability & Data Contracts
Last updated Aug 28, 2026. Interested? Apply on the company site.

About Apple

Discover the innovative world of Apple and shop everything iPhone, iPad, Apple Watch, Mac, and Apple TV, plus explore accessories, entertainment, and expert device support.

Discover the innovative world of Apple and shop everything iPhone, iPad, Apple Watch, Mac, and Apple TV, plus explore accessories, entertainment, and expert device support.

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