Senior Data Engineer — Real-Time AI Ad Tech Pipelines

Disney Entertainment

Glendale (CA)

On-site

USD 144,000 - 193,000

Full time

6 days ago
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Benefits offered by this job

Disney employee benefits

Job summary

Disney Entertainment and ESPN Product & Technology is seeking a Senior Data Engineer in Glendale, CA to design, build, and scale data pipelines powering AI-enabled ad tech and data platforms. You will own streaming architectures, vector stores, and real-time data foundations for high-profile applications.

You will collaborate across AI engineering, infra, and product teams, mentor junior engineers, and help deliver reliable, production-grade data solutions in a fast-paced environment.

Qualifications

  • 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.
  • Familiarity with testing, monitoring, and automation for data pipelines.

Responsibilities

  • Build and maintain high-performance streaming and batch data pipelines that power AI applications, ensuring reliable low-latency ingestion and high-throughput processing.
  • 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.
  • Implement robust data quality validation, schema evolution safeguards, and governance/compliance controls.
  • 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.
  • Influence design direction through technical proposals and hands-on delivery rather than formal ownership of standards.

Skills

Data engineering
Streaming pipelines
Python
Java
SQL
Kafka
Flink
Spark
Kinesis
Embedding pipelines
Vector stores
Airflow
Dagster
Collaboration

Education

Bachelor or above in computer science or related quantitative field

Tools

Pinecone
Weaviate
FAISS
pgvector
LangChain
LangGraph
Databricks
Kafka
Kubernetes
S3
Glue
MWAA

Job description

Disney Entertainment and ESPN Product & Technology is seeking a Senior Data Engineer in Glendale, CA to design, build, and scale data pipelines powering AI-enabled ad tech and data platforms. You will own streaming architectures, vector stores, and real-time data foundations for high-profile applications.

You will collaborate across AI engineering, infra, and product teams, mentor junior engineers, and help deliver reliable, production-grade data solutions in a fast-paced environment.

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