Data Engineering at The Walt Disney Company

Roles, Comp & Culture

An L6 staff data engineer at The Walt Disney Company sits around $304K total comp from 59 verified salary datapoints. The primary Data Engineering tech consists of AWS, Airflow and Snowflake, according to current job listings. The Walt Disney Company pays data engineers slightly below other Media companies. Reviews put them at 3.8 on Glassdoor, a little above the middle of the pack. Employee sentiment at The Walt Disney Company reads neutral and employee happiness is trending down over the past year. Layoff risk scores low for the next 30 days. 19 data engineering roles are open right now.

Last updated: Proudly published by: Jeff Wahl

The Walt Disney Company data engineer compensation

Each level's figure is the median of individual The Walt Disney Company offers at that level, so it reflects a typical outcome rather than an average pulled up by a few large packages. Total comp counts base salary plus equity and bonus annualized over the vest, and the range shown is the middle half of offers, with the top and bottom quarters trimmed off.

L3Entry$166Kmedian
Base$156KRange$153K–$168KReports8 · 0-2 yrsThe Walt Disney Company loop
L4Mid$205Kmedian
Base$154KRange$131K–$250KReports30 · 2-5 yrsThe Walt Disney Company loop
L5Senior$214Kmedian
Base$162KRange$195K–$284KReports17 · 5-10 yrsThe Walt Disney Company loop
L6Staff$304Kmedian
Base$208KRange$218K–$334KReports6 · 8-15 yrsThe Walt Disney Company loop
Updated 59 verified salary reports + 2 salaries adjusted to total comp

The Walt Disney Company employee sentiment, tracked weekly

Employee happiness for data engineers over the past year, so you can see which direction it is moving, not just where it sits today.

Neutraltrending down over the past year
20252026
Updated The Walt Disney Company employee happiness

Recent The Walt Disney Company events

Layoffs, leadership changes, and other major moves at the company, with dates.

  1. LayoffMay 2026Layoff
  2. LayoffMay 2026Layoff
  3. Exec departureMar 2026Leadership change
  4. Exec departureFeb 2026Leadership change
  5. Exec departureFeb 2026Leadership change
  6. Exec departureNov 2025Leadership change
  7. Exec departureOct 2025Leadership change
  8. Exec departureOct 2025Leadership change
Updated 8 The Walt Disney Company events, 2 with headcount

Notable company events we track, with dates.

The Walt Disney Company data engineering tech stack

The languages, storage, and processing tools The Walt Disney Company data engineers actually work with, grouped by what they do. Tailor your system-design answers to this stack.

Languages
Python
SQLSQL
Java
Scala
PySpark
Bash
Warehouse / SQL
Snowflake
Table formats
Delta Lake
Streaming
Kinesis
Flink
Kafka
Orchestration
Airflow
CI/CD
Compute
Spark
Databricks
Lambda
Storage
S3
Cloud
AWS
Azure
Other
Glue
Updated from current job listings

The Walt Disney Company data engineer job openings

A live read on what they are hiring: open roles, recent postings, where, and at what level.

Practice for the The Walt Disney Company loop

Round by round, the problems our model predicts for this company's interview. Rehearse the shapes their panels keep returning to.

Preparing for the The Walt Disney Company loop

The round-by-round process, example questions, and prep plan are on the interview guide.

Compare The Walt Disney Company with other data engineering employers

How the role, pay, and loop stack up against peer companies.

02 / Why practice

Prepare at The Walt Disney Company interview difficulty

  1. 01

    Reading a solution is not the same as writing one

    Every engineer who has frozen on a query they had read a dozen times knows the gap. The only preparation that closes it is producing the answer yourself, under time, before the interview does it for you

  2. 02

    76% of hiring managers reject on the coding task, not the resume

    From HackerRank's 2024 Developer Skills Report. Candidates who look strong on paper still fail the live screen if they haven't done timed, executable practice

  3. 03

    5 problem shapes cover 80% of data engineer loops

    Dedup, sessionization, top-N-per-group, slowly-changing dimensions, partition tricks. Writing the shapes by hand turns the unfamiliar into pattern recognition

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