Sr Data Engineer

Disney Disney · Media · Glendale, CA +4

Senior Data Engineer responsible for designing, building, and scaling data foundations that power AI adoption across Ad Technology. This includes owning data flow into AI-ready stores, streaming pipelines, embedding pipelines, vector stores, and monitoring systems. The role involves partnering with AI Core Engineering to enable shared agents and developer tools with robust, real-time data, and mentoring junior team members.

What you'd actually do

  1. Build and maintain high‑performance streaming and batch data pipelines that power AI applications, ensuring reliable low‑latency ingestion and high‑throughput processing.
  2. Implement and extend embedding generation workflows, vector store integrations, and retrieval pipelines supporting semantic search, RAG systems, and AI assistants.
  3. Develop and optimize scalable storage and retrieval patterns, focusing on cost‑efficient architecture and smooth production performance.
  4. Implement AI‑optimized data models and storage patterns that align with broader enterprise architecture and platform requirements.
  5. Integrate pipelines with shared AI platform services (agent frameworks, registries, feature stores), ensuring clean, versioned, and reliable data delivery.

Skills

Required

  • 5+ years of data engineering experience
  • 1+ year in a lead or senior technical role
  • Experience building and scaling streaming data pipelines in large-scale, distributed environments
  • Strong skills in Python, Java and SQL
  • Expert level skill in either Python or Java

Nice to have

  • Python
  • Java
  • SQL
  • streaming data pipelines
  • distributed environments
  • embedding generation
  • vector store integrations
  • RAG systems
  • AI assistants
  • semantic search
  • AI-optimized data models
  • AI platform services
  • observability
  • data quality validation
  • schema evolution
  • governance/compliance controls

What the JD emphasized

  • AI adoption
  • embedding generation
  • vector store integrations
  • RAG systems
  • AI assistants
  • real-time data
  • AI-optimized data models
  • AI platform services

Other signals

  • AI adoption
  • data foundations
  • embedding generation
  • vector stores
  • RAG systems
  • AI assistants
  • real-time data