Data Engineering at Snap
Roles, Comp & Culture
An L6 staff data engineer at Snap sits around $680K total comp from 38 verified salary datapoints. The primary Data Engineering tech consists of AWS, S3 and Spark, according to current job listings. Snap pays data engineers above other Technology companies. Reviews put them at 3.4 on Glassdoor, toward the bottom of the pack. Snap employees are stressed and employee happiness is trending down over the past year. Layoff risk scores low for the next 30 days. 31 data engineering roles are open right now.
Snap data engineer compensation
Each level's figure is the median of individual Snap 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.
Snap 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.
Recent Snap events
Layoffs, leadership changes, and other major moves at the company, with dates.
- LayoffJun 2026Layoff
- Exec departureMay 2026Leadership change
- Exec departureApr 2026Leadership change
- LayoffApr 2026~73 roles cut
- LayoffApr 2026Layoff
- LayoffApr 2026Layoff
- Exec departureFeb 2026Leadership change
- Exec departureDec 2025Leadership change
- Exec departureSep 2025Leadership change
- Exec departureAug 2025Leadership change
- Exec departureMay 2025Leadership change
Notable company events we track, with dates.
Snap data engineering tech stack
The languages, storage, and processing tools Snap data engineers actually work with, grouped by what they do. Tailor your system-design answers to this stack.
SQL
Iceberg
Data FactorySnap data engineer job openings
A live read on what they are hiring: open roles, recent postings, where, and at what level.
Define and lead enterprise data migration strategies from SQL Server, DB2, and AS/400 platforms to Snowflake.
Build, automate, and maintain resilient pipelines for cleaning, validating, and transforming batch and streaming data that feed into medallion architectures.
Create AI sympathetic annotations to new and existing data sets
Develop and maintain data pipelines using Python, SQL, Snowflake, and AWS
Build scalable ETL/ELT pipelines using AWS Glue, Lambda, Step Functions, EMR, or Apache Spark
Design advanced distributed data processing solutions using Python and PySpark to deliver reliable batch and streaming pipelines that support key business analytics needs
· Architect scalable data solutions leveraging AWS services such as Glue, Redshift, S3, EMR, Lambda, Aurora, and Kinesis.
Design, build, and maintain scalable ETL pipelines and cloud-based data architectures
Design, build, and operate scalable, cloud‑native data platforms supporting batch and streaming use cases, with strong focus on governance, performance, and reliability.
Design and implement scalable ETL/ELT pipelines and data transformation frameworks using AWS-native services including Glue, EMR, Lambda, and Kinesis.
Preparing for the Snap loop
The round-by-round process, example questions, and prep plan are on the interview guide.
Compare Snap with other data engineering employers
How the role, pay, and loop stack up against peer companies.
Prepare at Snap interview difficulty
- 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
- 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
- 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