Databricks
Large (~7,000)
Datadog
Large (~6,000)
Best For
Databricks
Best for: Data engineers who want strong comp and deep technical pedigree at scale
Datadog
Best for: Engineers who want strong comp and interesting scale challenges in cloud observability
Ratings
DatabricksDatadog
4.1
4.2
Overall
3.9
3.8
Work-Life Balance
4.0
4.3
Culture & Values
4.3
4.4
Comp & Benefits
3.8
3.8
Senior Mgmt
3.9
4.0
Career Opps
👍 82% Recommend
👤 88% CEO Approval (Ali Ghodsi)
👍 80% Recommend
👤 87% CEO Approval (Olivier Pomel)
Culture Values
Databricks only
🌈 Diverse & Inclusive
Datadog only
🚀 Ship Fast & Iterate
Shared
⚙️ Engineering-Driven🌱 Learning & Growth💎 Strong Comp & Equity🎯 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
Datadog
- Excellent compensation and equity — stock has been a genuine wealth builder for early employees
- Strong engineering culture with smart coworkers and interesting technical challenges at scale
- Fast pace can lead to long hours and pressure to deliver, work-life balance varies by team
- Rapid growth has led to organizational growing pains and bureaucracy creeping in
Bottom Line
Databricks
Choose Databricks if you want elite data infrastructure work with strong equity — but brace for constant org changes.
Datadog
Choose Datadog if you want strong comp, interesting scale challenges in observability, and a fast-paced engineering culture — but expect long hours and growing bureaucracy.
Open Roles
Databricks — 836 jobs
💼 Sales / GTM
359
💻 Engineering
271
📋 Product
49
📊 Data
23
⚙️ Operations
17
📣 Marketing
13
🧠 ML / AI
12
👤 HR / People
9
🎨 Design
6
💰 Finance
6
⚖️ Legal
5
🎧 Support
1
Datadog — 451 jobs
💼 Sales / GTM
217
💻 Engineering
118
📋 Product
28
📣 Marketing
15
👤 HR / People
8
🧠 ML / AI
8
🎨 Design
7
⚙️ Operations
6
⚖️ Legal
3
📊 Data
1
💰 Finance
1
Summary
Databricks scores 4.1/5.0 on Glassdoor with a 3.9 work-life balance rating. Datadog scores 4.2/5.0 overall with a 3.8 WLB. That’s a 0.1-point gap on overall satisfaction.
Both companies share these culture values: Engineering-Driven, Learning & Growth, Strong Comp & Equity, Direct Product Impact. Databricks also emphasizes Diverse & Inclusive. Datadog also emphasizes Ship Fast & Iterate.
On the hiring front, Databricks has 836 open roles and Datadog has 451 open roles.