Databricks
Large (~7,000)
Sierra
Large (~500)
Best For
Databricks
Best for: Data engineers who want strong comp and deep technical pedigree at scale
Sierra
Best for: Builders who want to work with proven Salesforce and Google leadership on enterprise AI agents
Ratings
DatabricksSierra
4.1
4.0
Overall
3.9
3.5
Work-Life Balance
4.0
4.1
Culture & Values
4.3
4.0
Comp & Benefits
3.8
3.8
Senior Mgmt
3.9
3.8
Career Opps
👍 82% Recommend
👤 88% CEO Approval (Ali Ghodsi)
👍 80% Recommend
👤 84% CEO Approval (Bret Taylor)
Culture Values
Databricks only
🌈 Diverse & Inclusive🎯 Direct Product Impact
Sierra only
🚀 Ship Fast & Iterate
Shared
⚙️ Engineering-Driven🌱 Learning & Growth💎 Strong Comp & Equity
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
Sierra
- Elite founders with proven track records
- Strong equity at $10B valuation
- In-person-first culture
- Competitive intensity may not suit everyone
Bottom Line
Databricks
Choose Databricks if you want elite data infrastructure work with strong equity — but brace for constant org changes.
Sierra
Choose Sierra if you want elite founders (Bret Taylor, Clay Bavor) and strong equity at a $10B enterprise AI company — but it's in-person-first and the competitive intensity won't suit everyone.
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
Sierra — 134 jobs
💻 Engineering
42
💼 Sales / GTM
27
📋 Product
15
👤 HR / People
7
🎨 Design
5
⚖️ Legal
5
📣 Marketing
5
⚙️ Operations
5
📊 Data
2
💰 Finance
1
Summary
Databricks scores 4.1/5.0 on Glassdoor with a 3.9 work-life balance rating. Sierra scores 4.0/5.0 overall with a 3.5 WLB. That’s a 0.1-point gap on overall satisfaction.
Both companies share these culture values: Engineering-Driven, Learning & Growth, Strong Comp & Equity. Databricks also emphasizes Diverse & Inclusive, Direct Product Impact. Sierra also emphasizes Ship Fast & Iterate.
On the hiring front, Databricks has 842 open roles and Sierra has 134 open roles.