This role pays less than
60%
of similar roles. Most pay
$129,145–$207,637
— the shaded band above.
At the midpoint, this role pays about
$158k
versus about
$168k
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.
The Lead Data Engineer joins the Decision Science and Integration team to plan and lead research and development for advanced analytic data solutions utilizing GenAI. This role involves collaborating with business and technology leaders to translate high-level requirements into technical tasks, designing and delivering necessary data pipelines, and managing the full lifecycle of production rollout and sustainment. The candidate will work with various tools including SQL, Python, Snowflake, PostgreSQL, Apache Airflow, Docker, and Kubernetes while navigating concepts like Knowledge Graphs and Data Mesh. The position focuses on solving complex data engineering problems to support advanced analytic processes across diverse business units. Key responsibilities include performing hands-on development, leading design reviews, and managing ELT/ETL pipeline maintenance within a multi-team environment to provide sophisticated data infrastructure for the organization's decision-making tools.
Lead research and development for advanced analytic data solutions utilizing GenAI technologies.
Translate high-level business requirements into technical data engineering tasks and specifications.
Design, develop, and maintain complex ELT/ETL data pipelines across multiple environments.
Build and manage relational databases using platforms like Snowflake or PostgreSQL.
Orchestrate and deploy code using tools such as Apache Airflow and containerization technologies like Docker.
Define technical architectures for GenAI systems including model selection and pipeline orchestration.
Lead design reviews and communicate technical concepts to non-technical stakeholders.
Manage project lifecycles including estimation, sprint planning, testing, and production rollout.
What we're looking for
Bachelor's degree in computer science, Information Systems, Software, Electrical or Electronics Engineering, or a comparable field of study and/or equivalent work experience.
7+ years of experience in data engineering development using multiple environments and DevOps procedures for code deployment.
Multiple years of experience with ELT/ETL data pipeline development and maintenance.
Multiple years of experience using SQL and Python.
3+ years of experience designing and building relational databases, preferably Snowflake or PostgreSQL.
3+ years of experience leading and deploying code using a source control product such as GitLab or GitHub.
2+ years of experience with job scheduling software like Apache Airflow, Amazon MWAA, GitLab Runners, or UC4.
Experience with containerization technologies such as Docker or Kubernetes; experience with GenAI systems, architectures, and AWS cloud technologies (preferred).