Job Description

Job Summary:

Disney Entertainment and ESPN Product & Technology

Technology is at the heart of Disney’s past, present, and future. Disney Entertainment and ESPN Product & Technology is a global organization of engineers, product developers, designers, technologists, data scientists, and more – all working to build and advance the technological backbone for Disney’s media business globally.

The team marries technology with creativity to build world-class products, enhance storytelling, and drive velocity, innovation, and scalability for our businesses. We are Storytellers and Innovators. Creators and Builders. Entertainers and Engineers. We work with every part of The Walt Disney Company’s media portfolio to advance the technological foundation and consumer media touch points serving millions of people around the world.

Here are a few reasons why we think you’d love working here:

Building the future of Disney’s media: Our Technologists are designing and building the products and platforms that will power our media, advertising, and distribution businesses for years to come.

Reach, Scale & Impact: More than ever, Disney’s technology and products serve as a signature doorway for fans' connections with the company’s brands and stories. Disney+. Hulu. ESPN. ABC. ABC News…and many more. These products and brands – and the unmatched stories, storytellers, and events they carry – matter to millions of people globally.

3. Innovation: We develop and implement groundbreaking products and techniques that shape industry norms, and solve complex and distinctive technical problems.

Ad Platforms is responsible for Disney’s industry-leading ad technology and products – driving advertising performance, innovation, and value in Disney’s sports, news, and entertainment content, across all media platforms.

Job Summary:

We are hiring a Lead Data Engineer to design, build, and scale the data foundations that power AI adoption across Ad Technology. In this role, you will own how data flows into AI- ready and optimized stores, from streaming pipelines and embedding pipelines to vector stores and monitoring systems.

You’ll partner closely with the AI Core Engineering team to enable shared agents, registries, and developer tools with robust, reliable, real-time data. As a technical leader, you will set data engineering patterns, mentor engineers, and deliver resilient pipelines that support high-profile AI applications with speed and safety. This role ensures AI applications are powered by reliable, real-time data foundations, enabling faster and safer deployments across Disney Ad Tech.

Responsibilities and Duties of the Role:

Data Architecture & Pipeline Development

• Design and build streaming and batch pipelines for AI applications, ensuring low-latency and high-throughput data flows.
• Implement embedding pipelines and vector store integrations to support retrieval, semantic search, and AI assistants.
• Optimize storage and retrieval patterns for scalability, compliance, and cost efficiency.

AI Data Foundations & Integration

• Own the design of AI-optimized data stores that align with enterprise data architecture.
• Partner with the AI Core Engineering team to provide reliable pipelines into shared agents, registries, and services.
• Develop reusable data ingestion and transformation frameworks for cross- team adoption.

Monitoring, Quality & Reliability

• Build observability into data pipelines with monitoring, alerting, and dashboards for latency, drift, and failures.
• Implement data quality checks, schema validation, and governance controls.
• Ensure pipelines meet enterprise standards for compliance, audit, and resilience.

Leadership & Collaboration

• Mentor engineers, conduct design/code reviews, and enforce data engineering best practices.
• Collaborate with infra, product, and governance teams to align on priorities and safe adoption of AI.
• Drive delivery of high-profile AI applications by balancing execution speed with system reliability.

Required Education, Experience/Skills/Training:

Basic Qualifications

• 7+ years of data engineering experience, with at least 2 years 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.

Preferred Qualifications

• Experience integrating AI-ready data stores with LLM orchestration frameworks (LangChain, LangGraph, etc.).
• Knowledge of observability and monitoring stacks (Datadog, Prometheus, or equivalent).
• Background in governance and compliance practices for enterprise data platforms.
• Experience building data frameworks, registries, or accelerators adopted by multiple teams.
• Experience ensuring data security, lineage, and auditability in enterprise data environments
• Skilled at writing design documentation, driving system architecture reviews, and influencing data engineering culture.

Required Education

• Bachelor’s degree in Computer Science, Engineering, or related technical field (Master’s preferred), or equivalent experience.

The hiring range for this position in Glendale, CA is $152,200 - $204,100 per year and in Seattle, WA is $159,500 - $213,900 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.

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