Databricks
Large (~7,000)
Linear
Small (~80)
Best For
Databricks
Best for: Data engineers who want strong comp and deep technical pedigree at scale
Linear
Best for: Craftspeople who value deep work, async communication, and minimal meetings
Ratings
DatabricksLinear
4.1
4.6
Overall
3.9
4.4
Work-Life Balance
4.0
4.8
Culture & Values
4.3
4.3
Comp & Benefits
3.8
4.5
Senior Mgmt
3.9
4.0
Career Opps
👍 82% Recommend
👤 88% CEO Approval (Ali Ghodsi)
👍 95% Recommend
👤 95% CEO Approval (Karri Saarinen)
Culture Values
Databricks only
🌱 Learning & Growth💎 Strong Comp & Equity🌈 Diverse & Inclusive
Linear only
🎧 Deep Work / Low Meetings🌐 Remote-Friendly📡 Async-First⚖️ Work-Life Balance
Shared
⚙️ Engineering-Driven🎯 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
Linear
- Obsessive product craft — building the best-in-class PM tool teams genuinely love
- Deep work culture with no standups and minimal meetings — actually practiced
- Very small team = limited roles available at any given time
- High hiring bar means slow growth — patience required
Bottom Line
Databricks
Choose Databricks if you want elite data infrastructure work with strong equity — but brace for constant org changes.
Linear
Choose Linear if you want obsessive product craft with genuine work-life balance — but the team is tiny and hiring bar is extreme.
Open Roles
Databricks — 789 jobs
💼 Sales / GTM
319
💻 Engineering
258
📋 Product
52
📊 Data
23
⚙️ Operations
17
🧠 ML / AI
15
💰 Finance
12
📣 Marketing
11
👤 HR / People
9
⚖️ Legal
5
🎨 Design
4
🎧 Support
1
Linear — 21 jobs
💼 Sales / GTM
6
💻 Engineering
5
🎨 Design
3
📣 Marketing
3
📋 Product
2
⚖️ Legal
1
🎧 Support
1