Senior Data Engineer

The Walt Disney Company

Senior Data Engineer at Disney developing data foundations for AI-driven advertising solutions. Collaborating with cross-functional teams and optimizing data pipelines for advertising technologies.

Posted 6/6/2026full-timeGlendale • California, Washington • 🇺🇸 United StatesSenior💰 $138,900 - $186,200 per yearWebsite

Tech Stack

Tools & technologies

AirflowJavaKafkaPythonSparkSQL

About the role

Key responsibilities & impact

Build and maintain high‑performance streaming and batch data pipelines that power AI applications
Implement and extend embedding generation workflows, vector store integrations, and retrieval pipelines supporting semantic search, RAG systems, and AI assistants
Develop and optimize scalable storage and retrieval patterns, focusing on cost‑efficient architecture and smooth production performance
Implement AI‑optimized data models and storage patterns that align with broader enterprise architecture and platform requirements
Integrate pipelines with shared AI platform services (agent frameworks, registries, feature stores), ensuring clean, versioned, and reliable data delivery
Build reusable ingestion, transformation, and data processing components that streamline adoption across engineering teams
Embed end‑to‑end observability into data systems, including metrics, structured logging, automated alerts, drift detection, and failure analysis
Ensure deployed pipelines meet high standards for reliability, recoverability, auditability, and long‑term maintenance
Drive execution by owning the full development lifecycle: prototyping, implementation, testing, deployment, optimization, and documentation
Collaborate closely with infrastructure, ML engineering, product, and governance teams to deliver production‑ready AI capabilities
Lead by example through strong execution, high‑quality code, and proactive problem solving

Requirements

What you’ll need

5+ years of data engineering experience, with at least 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 with expert level skill in either Python or Java
Proven experience building streaming data pipelines (e.g., Kafka, Flink, Spark, Kinesis)
Experience with embedding pipelines and vector stores (e.g., Pinecone, Weaviate, FAISS, pgvector)
Strong knowledge of data modeling, storage optimization, and retrieval patterns for large-scale systems
Hands-on experience with workflow orchestration tools (Airflow, Dagster, etc.)
Strong collaboration and communication skills, able to partner across AI engineering, infra, and product teams

Benefits

Comp & perks

Bonus and/or long-term incentive units may be provided as part of the compensation package
Full range of medical, financial, and/or other benefits

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Hard Skills & Tools

data engineeringstreaming data pipelinesPythonJavaSQLdata modelingstorage optimizationretrieval patternsworkflow orchestrationembedding generation

Soft Skills

collaborationcommunicationproblem solvingleadershipexecution