Data Engineer

The Walt Disney Company

Confirmed live today High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Lake Buena Vista, FLBurbank, CA
Salary
$106,900–$143,300 / yr
Employment
Full-time
Posted
3 days ago
Freshness
Confirmed live today
Closes
Oct 17, 2026

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $165k
This role $125k
$95k most similar roles pay here $216k

This role pays less than 86% of similar roles. Most pay $126,800–$203,150 — the shaded band above. At the midpoint, this role pays about $125k versus about $165k for comparable roles.

Based on 240 similar postings.

Employer

About The Walt Disney Company

The Walt Disney Company is a diversified global entertainment and media enterprise operating in segments including Disney Parks, Experiences and Products; Entertainment (ABC, Hulu, Disney+); and ESPN. Industry: Entertainment & Media

The Walt Disney Company currently has 127 open roles on FindRole.

Listed pay typically runs $148,300–$190,300 across 127 roles with salary data.

Most-posted roles

View all roles at The Walt Disney Company

At a glance

TL;DR · Data Engineer

As a Data Engineer on the Decision Science and Integration team, you will contribute to development, sustainment projects, prototyping, and research initiatives by providing essential data pipeline services. You will collaborate with business, science, and technology teams to gather requirements and design data pipelines that aggregate and manipulate information for use in science models, visualizations, and applications. The role involves integrating GenAI tools into engineering processes to enhance automation and delivering AI-based solutions. Key technical requirements include proficiency in Python, SQL, and ELT/ETL pipeline development, along with experience in source-to-target mapping and multi-environment DevOps procedures. You will work with platforms like Snowflake, PostgreSQL, Databricks, and Apache Airflow while utilizing tools such as GitLab or GitHub. The role addresses the challenge of transforming complex data into actionable insights for entertainment, sports, and theme park operations.

What does a Data Engineer earn in California?

Median $198275 from 41 postings across 18 companies.

See salary data

What you'll do

  • Design and deliver data pipelines to support advanced analytics, science models, and visualizations.
  • Develop, enhance, and implement systems for processing and manipulating large datasets.
  • Integrate GenAI tools and techniques into data engineering processes to improve automation.
  • Deliver AI-based solutions using technologies like LLMs, vector databases, and RAG architectures.
  • Perform source-to-target mapping and maintain ELT/ETL pipelines across multiple environments.
  • Manage and deploy code using source control systems and DevOps procedures.
  • Translate complex business requirements into technical data solutions for non-technical stakeholders.
  • Build and manage data warehouse structures using platforms like Snowflake or PostgreSQL.

What we're looking for

  • Bachelor's degree in computer science, Information Systems, Software, Electrical or Electronics Engineering, or equivalent experience.
  • 3+ years of experience in technology roles, preferably in data engineering.
  • Strong experience with ELT/ETL data pipeline development, maintenance, and source-to-target mapping.
  • Proven expertise using Python and SQL.
  • Familiarity with GenAI concepts and tools such as LLMs, embeddings, and prompt engineering.
  • Experience developing in multi-environment setups (Dev, QA, Prod) and utilizing DevOps procedures for code deployment.
  • Proficiency in database/data warehouse design and platforms like PostgreSQL or Snowflake.
  • Experience managing and deploying code using source control products like GitLab or GitHub.
  • Ability to communicate complex technical concepts to non-technical team members.
  • Understanding of vector databases, RAG architectures, or GenAI frameworks like LangChain (preferred).
  • Experience with big data technologies, API development, or orchestration tools like Apache Airflow (preferred).
  • Knowledge of cloud architecture (preferably AWS) and containerization technologies like Docker or Kubernetes (preferred).

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