Databricks
Large (~7,000)
Scale AI
Large (~1,200)
Best For
Databricks
Best for: Data engineers who want strong comp and deep technical pedigree at scale
Scale AI
Best for: Ambitious builders who want critical AI infrastructure work serving top-tier clients
Ratings
DatabricksScale AI
4.1
3.5
Overall
3.9
2.7
Work-Life Balance
4.0
2.9
Culture & Values
4.3
3.5
Comp & Benefits
3.8
2.8
Senior Mgmt
3.9
3.6
Career Opps
👍 82% Recommend
👤 88% CEO Approval (Ali Ghodsi)
👍 56% Recommend
👤 60% CEO Approval (Alexandr Wang)
Culture Values
Databricks only
💎 Strong Comp & Equity🌈 Diverse & Inclusive
Scale AI only
🚀 Ship Fast & Iterate
Shared
⚙️ Engineering-Driven🌱 Learning & Growth🎯 Direct Product Impact
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
Scale AI
- Building critical AI data infrastructure used by OpenAI, Meta, Microsoft, and the US government
- Strong compensation for engineers — competitive base + equity
- Work-life balance rated 2.7/5 — long hours common during client deadlines
- Culture and values scored 2.9/5 — inconsistent management quality
Bottom Line
Databricks
Choose Databricks if you want elite data infrastructure work with strong equity — but brace for constant org changes.
Scale AI
Choose Scale AI if you want to build data infrastructure for OpenAI and the US government — but expect long hours and inconsistent management.
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
Scale AI — 175 jobs
💻 Engineering
64
🧠 ML / AI
25
📋 Product
16
💼 Sales / GTM
14
⚙️ Operations
7
⚖️ Legal
5
📣 Marketing
4
📊 Data
2
💰 Finance
2
👤 HR / People
2
🎨 Design
1
🎧 Support
1
Summary
Databricks scores 4.1/5.0 on Glassdoor with a 3.9 work-life balance rating. Scale AI scores 3.5/5.0 overall with a 2.7 WLB. That’s a 0.6-point gap on overall satisfaction.
Both companies share these culture values: Engineering-Driven, Learning & Growth, Direct Product Impact. Databricks also emphasizes Strong Comp & Equity, Diverse & Inclusive. Scale AI also emphasizes Ship Fast & Iterate.
On the hiring front, Databricks has 842 open roles and Scale AI has 175 open roles.