Databricks
Large (~7,000)
Snowflake
Large (~7,000)
Best For
Databricks
Best for: Data engineers who want strong comp and deep technical pedigree at scale
Snowflake
Best for: Professionals interested in Snowflake
Ratings
DatabricksSnowflake
4.1
3.7
Overall
3.9
3.4
Work-Life Balance
4.0
3.8
Culture & Values
4.3
3.7
Comp & Benefits
3.8
3.5
Senior Mgmt
3.9
3.5
Career Opps
👍 82% Recommend
👤 88% CEO Approval (Ali Ghodsi)
👍 74% Recommend
👤 78% CEO Approval (CEO)
Culture Values
Databricks only
🌈 Diverse & Inclusive🎯 Direct Product Impact
Snowflake only
🚀 Ship Fast & Iterate
Shared
⚙️ Engineering-Driven🌱 Learning & Growth💎 Strong Comp & Equity
Pros & Cons
Databricks
- Engineers who built Spark, Delta Lake, MLflow — deep technical pedigree
- Strong compensation and equity packages consistently above market
- Hypergrowth means org changes are constant — teams restructure frequently
- Some legacy Spark-era tech debt that can slow down new features
Snowflake
- Massive-scale distributed systems work with top-tier compensation and RSUs
- High technical bar, accessible senior leaders, and real learning opportunities
- Culture shifting under new leadership — holiday cuts and increased performance pressure
- Quarterly planning overhead and oncall load vary significantly by team
Bottom Line
Databricks
Choose Databricks if you want elite data infrastructure work with strong equity — but brace for constant org changes.
Snowflake
Snowflake — check Glassdoor for detailed reviews.
Open Roles
Databricks — 842 jobs
💼 Sales / GTM
353
💻 Engineering
284
📋 Product
39
📣 Marketing
34
📊 Data
22
👤 HR / People
12
🧠 ML / AI
12
⚙️ Operations
11
🎨 Design
6
💰 Finance
5
⚖️ Legal
5
Snowflake — 419 jobs
💻 Engineering
181
💼 Sales / GTM
93
📣 Marketing
29
📋 Product
22
📊 Data
14
⚖️ Legal
6
⚙️ Operations
6
🧠 ML / AI
5
💰 Finance
3
🎨 Design
2
Summary
Databricks scores 4.1/5.0 on Glassdoor with a 3.9 work-life balance rating. Snowflake scores 3.7/5.0 overall with a 3.4 WLB. That’s a 0.4-point gap on overall satisfaction.
Both companies share these culture values: Engineering-Driven, Learning & Growth, Strong Comp & Equity. Databricks also emphasizes Diverse & Inclusive, Direct Product Impact. Snowflake also emphasizes Ship Fast & Iterate.
On the hiring front, Databricks has 842 open roles and Snowflake has 419 open roles.