Databricks · Primly Community

how I'd prep for the Databricks interview if I started over

remote_swe_42 · 6 replies

Just closed an offer from Databricks (L5, remote, Bay Area-adjusted comp) after a process that started in late January 2026. Here's the prep breakdown I'd run if I were starting from scratch, in priority order.

Week 1: Domain before DSA.

Read the Delta Lake paper. Read their blog posts on structured streaming and the Photon engine. Watch the Data + AI Summit talks that their own engineers gave. You are interviewing at a data infrastructure company. The system design rounds will go much better if you've internalized the actual tradeoffs they've already solved. This is not optional.

Week 2: Spark specifically.

Not just PySpark syntax. Understand the execution model: DAG planning, shuffle operations, why certain transformations are wide vs narrow, how to avoid data skew. Practice writing actual Spark jobs against real datasets. If you've only seen Spark in a notebook tutorial, that's not enough for the coding rounds. The take-home challenge (if they give you one for your track) involves real data at meaningful scale.

Week 3: Classic LC but targeted.

Two coding rounds. The problems I saw were medium-to-hard in complexity but graph and tree-heavy, less purely dynamic programming than some companies. Practice on graphs especially, BFS/DFS, topological sort. String manipulation problems showed up too.

Behavioral round:

Databricks is speed of execution as a core value, and they assess it behaviorally. Prepare stories with clear metrics where you shipped fast under constraints. Vague 'we improved performance' stories don't work here. 'We reduced p99 latency from 800ms to 120ms in six weeks' works.

The debrief:

My recruiter told me decisions are typically made within 48-72 hours of the final round. If you haven't heard by day four, it's okay to follow up.

Comp for my L5 offer: base around $210k, RSUs that vest over 4 years with a one-year cliff. Total package in the $380-420k TC range depending on stock price. I did not negotiate hard enough on RSU grant size, in retrospect.

Happy to answer specific questions on the process.

6 replies

frontend_fran

the 'domain before DSA' framing is genuinely useful. I've been doing it backward every time. Just spending two weeks on neetcode and then showing up to system design having never thought about the specific product. This thread is reorienting my whole prep order.

qa_quinn

L5 $380-420k TC range tracks with what I've seen from 2025-2026 data points. Bay Area adjusted remote is usually slightly below in-office SF/Seattle but not dramatically. Did they give you a choice on location designation or was remote the default for your role?

remote_swe_42

Role was posted as remote-US. They asked for my location and paid accordingly. No relocation discussed. Bay Area adjustment because I listed SF Bay as current location even though I work from home.

analyst_ana

how different is the prep for a data engineering vs SWE role? asking because I have a DE round scheduled and I'm not sure whether to focus more on the distributed systems side or the coding side.

remote_swe_42

for DE: heavily prioritize the Spark execution model, Delta Lake internals, and pipeline architecture. Coding is still there but the weight shifts toward data systems knowledge. The take-home for DE roles typically involves a real pipeline design or data quality problem, not just algorithms.

mobile_mara

genuinely curious how mobile/iOS fits into the Databricks loop. their product is pretty backend-heavy. did you see any mobile-track roles or is that basically not a thing there.