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: AI researchers who want world-class peers and Google-level benefits without sacrificing scientific rigor
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 (Demis Hassabis)
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
Brilliant research environment with strong work-life balance and excellent pay — but Google-scale bureaucracy and post-merger politics slow things down.
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
Google DeepMind — 84 jobs
🧠 ML / AI
24
📋 Product
18
🎨 Design
14
💻 Engineering
5
👤 HR / People
3
📊 Data
2
📣 Marketing
2
Summary
Databricks scores 4.1/5.0 on Glassdoor with a 3.9 work-life balance rating. Google DeepMind scores 4.2/5.0 overall with a 4.0 WLB. That’s a 0.1-point gap on overall satisfaction.
Both companies share these culture values: Engineering-Driven, Learning & Growth, Strong Comp & Equity, Diverse & Inclusive. Databricks also emphasizes Direct Product Impact. Google DeepMind also emphasizes Deep Work / Low Meetings, Ethical AI / Safety, Flexible Hours.
On the hiring front, Databricks has 842 open roles and Google DeepMind has 84 open roles.