Data Engineering at Amazon

Roles, Comp & Culture

An L7 principal data engineer at Amazon sits around $517K total comp from 3124 verified salary datapoints. The primary Data Engineering tech consists of AWS, Redshift and EMR, according to current job listings. Amazon pays data engineers above other Technology companies. Reviews put them at 3.5 on Glassdoor (toward the bottom of the pack) and negative sentiment on Blind. Employee sentiment at Amazon reads neutral and employee happiness is trending up over the past year. Layoff risk scores moderate for the next 30 days. 97 data engineering roles are open right now.

Last updated: Proudly published by: Jeff Wahl

Amazon

Technology · Seattle, LU · AMZN

live data · September 23, 2026

DE total comp

$237K median

L5 · senior level · $199K–$278K · 1319 verified datapoints

Hiring now

97 open DE roles

live from career pages

Team happiness

Neutral

employee happiness

Layoff risk (30d)

Moderate

Employee sentiment

Glassdoor3.5 / 5
BlindNegative

Employees

5,001–50,000

Amazon data engineer compensation

Each level's figure is the median of individual Amazon 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$147Kmedian
Base$124KRange$132K–$166KReports65 · 0-2 yrsAmazon loop →
L4Mid$180Kmedian
Base$136KRange$156K–$216KReports1315 · 2-5 yrsAmazon loop →
L5Senior$237Kmedian
Base$160KRange$199K–$278KReports1319 · 5-10 yrsAmazon loop →
L6Staff$360Kmedian
Base$196KRange$272K–$434KReports873 · 8-15 yrsAmazon loop →
L7Principal$517Kmedian
Base$230KRange$421K–$561KReports62 · 12+ yrsAmazon loop →
Updated 3124 verified salary reports + 510 salaries adjusted to total comp

What the Amazon signals mean

Sentiment tends to track team and org more than the company as a whole; the intensity, PIP reputation, and return-to-office posture weigh against the scale, mobility, and resume value of the AWS ecosystem.

Amazon 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 up over the past year
20252026
Updated Amazon employee happiness

Recent Amazon events

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

  1. LayoffJul 2026~616 roles cut
  2. LayoffApr 2026~72 roles cut
  3. LayoffApr 2026~87 roles cut
  4. LayoffMar 2026~132 roles cut
  5. LayoffJan 2026~16,000 roles cut
  6. LayoffJan 2026~126 roles cut
  7. LayoffDec 2025~84 roles cut
  8. LayoffOct 2025~14,000 roles cut
  9. LayoffAug 2025~325 roles cut
Updated 9 Amazon events, 9 with headcount

Notable company events we track, with dates.

Amazon data engineering tech stack

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

Languages
SQLSQL
Python
Scala
TypeScript
PySpark
Java
Warehouse / SQL
Redshift
Athena
DynamoDB
Hive
Streaming
Kinesis
Orchestration
Airflow
CI/CD
Informatica
Compute
EMR
Lambda
Spark
Storage
S3
Cloud
AWS
Other
Glue
Updated from current job listings

Amazon data engineer job openings

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

Amazon
Hiring now
Amazon data engineer · live from career pages
97
open roles
Amazon

AGS-AIT is looking for a Data Engineer to collaborate with cross-functional teams to design and develop data infrastructure and analytics capabilities for AGS AI and Automation initiatives.

L4ShanghaiNEW
Amazon

About the team Workforce Solutions (WS) empowers our customers by providing integrated, people-focused solutions that streamline hiring processes for WW Stores, AWS, Devices, and Talent Acquisition.

L4Bellevue7d ago
Amazon

As a Data Engineer on this team, you'll own the ingestion pipelines and the normalized dataset that everything else depends on.

L5Boulder7d ago
Amazon

Amazon's Selling Partner Insights and Analytics (SPIA) team is looking for an experienced Data Engineer to help architect and build the data platform that powers Paragon, Amazon's second-largest Human-in-the-Loop platform.

L4Bengaluru17d ago
Amazon

AWS’ Infrastructure Services - Supply Chain (AIS - SC) organization works to deliver futuristic solutions to source, build and maintain our socially responsible data center supply chains.

L5Bengaluru23d ago
Amazon

The AWS Analytics Engineering (AAE) organization is the analytics backbone of AWS — we build and operate the data platform that powers business decisions across more than 150 AWS services.

L5Seattle23d ago
Amazon

As a Senior Data Engineer, you will be a technical lead on the team, leading designs and mentoring engineerings on the team. you will create data models and ML data infrastructure that power our pricing algorithms and shape both customer and seller experiences.

L5Vancouver29d ago
Amazon

Design, develop, implement, test, document, and operate large-scale, high-volume, high-performance data structures for business intelligence analytics.

L5New York City56d ago
Amazon

About the team Sales Data Services team is part of Sales AI, a central data and science organization within Sales Intelligence, Technology, & Enablement organization (SITE) that powers Ad Sales selling motions and workflows via a suite of AI/ML services.

L4Bengaluru72d ago
Amazon

About the team The Advertising Sales Finance Analytics & FP&A team's responsibilities comprise of corporate reporting, planning, Headcount & OpEx, Goals reporting, and ad-hoc analysis.

L4Bengaluru78d ago
New postings per week
10
8/10
5
8/17
6
8/24
26
8/31
25
9/14
9
9/21
week beginning · ~27 weeks of data
Where they hire
Seattle
32
Bangalore
17
Washington DC
6
Los Angeles
5
Levels hiring
L45L55
Updated 97 open listings across 6 cities

Practice for the Amazon loop

The practice problems tagged with this company, grouped by domain and easiest first.

What makes Amazon different

The things about this company that should shape every answer you give.

Customer Obsession

Data engineers serve internal customers: analysts, data scientists, product managers. Amazon wants to hear how you prioritized their needs, understood their pain points, and delivered data products that solved real problems. Every behavioral answer should connect back to the person who used your work.

Ownership

You built it, you own it. Amazon expects data engineers to monitor their pipelines, respond to failures, and improve reliability without being asked. Stories about taking end-to-end responsibility for a data system, including the parts that were not your formal job, land hard with interviewers.

Dive Deep

When a pipeline breaks, do you look at the error message and restart it, or investigate the root cause? Amazon wants engineers who dig into the data, question anomalies, and understand their systems at a granular level. Bring stories about finding subtle bugs that others missed.

Bias for Action

Speed matters at Amazon. They want engineers who decide with 70% of the information rather than waiting for 100%. Share examples where you shipped a V1 quickly, gathered feedback, and iterated. Analysis paralysis is a red flag in Amazon interviews.

Earn Trust

Trust comes from delivering reliably and communicating honestly. Amazon interviewers look for candidates who admit mistakes, share credit, and are transparent about tradeoffs. If your pipeline had a data-quality issue, how you communicated it matters as much as how you fixed it.

Preparing for the Amazon loop

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

Amazon data engineer roles by level

Level-specific pages: the comp, the bar, and what the loop tests at each seniority.

Compare Amazon with other data engineering employers

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

02 / Why practice

Prepare at Amazon 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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