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 — 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
Linear — 19 jobs
💼 Sales / GTM
8
💻 Engineering
5
🎨 Design
3
📋 Product
2
⚖️ Legal
1
Summary
Databricks scores 4.1/5.0 on Glassdoor with a 3.9 work-life balance rating. Linear scores 4.6/5.0 overall with a 4.4 WLB. That’s a 0.5-point gap on overall satisfaction.
Both companies share these culture values: Engineering-Driven, Direct Product Impact. Databricks also emphasizes Learning & Growth, Strong Comp & Equity, Diverse & Inclusive. Linear also emphasizes Deep Work / Low Meetings, Remote-Friendly, Async-First, Work-Life Balance.
On the hiring front, Databricks has 842 open roles and Linear has 19 open roles.