Databricks
Large (~7,000)
Google DeepMind
Large (~7,000)
Best For
Databricks
Best for: Data engineers who want strong comp and deep technical pedigree at scale
Google DeepMind
Best for: Professionals interested in Google DeepMind
Ratings
DatabricksGoogle DeepMind
4.1
4.2
Overall
3.9
4.0
Work-Life Balance
4.0
4.3
Culture & Values
4.3
4.2
Comp & Benefits
3.8
4.0
Senior Mgmt
3.9
4.0
Career Opps
👍 82% Recommend
👤 88% CEO Approval (Ali Ghodsi)
👍 84% Recommend
👤 88% CEO Approval (CEO)
Culture Values
Databricks only
🎯 Direct Product Impact
Google DeepMind only
🎧 Deep Work / Low Meetings🤖 Ethical AI / Safety🕐 Flexible Hours
Shared
⚙️ Engineering-Driven🌱 Learning & Growth💎 Strong Comp & Equity🌈 Diverse & Inclusive
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
Google DeepMind
- World-class AI research environment with brilliant, collaborative colleagues
- Google-level compensation and benefits with genuine work-life balance
- Google-scale bureaucracy — slow decision-making compared to startups
- Large org means less individual ownership and impact on direction
Bottom Line
Databricks
Choose Databricks if you want elite data infrastructure work with strong equity — but brace for constant org changes.
Google DeepMind
Google DeepMind — check Glassdoor for detailed reviews.
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
Google DeepMind — 112 jobs
🧠 ML / AI
39
📋 Product
21
💻 Engineering
14
🎨 Design
8
📊 Data
5
👤 HR / People
2
📣 Marketing
2