Databricks

Healthy hybrid between small enough to move fast and have great individual impact, and big enough that it really matters to do things well and make room for specialists to grow their careers.

Good product direction and alignment across the company. Everyone feels like they're on the same team.

Politics exists, but at a rate much lower than in larger companies. Level-for-level, the challenges are significantly more technical and execution-oriented than organizational.

Meaningfully lower rate of low performers compared to my experience in past jobs. More focus and lower emphasis on non-constructive initiatives compared to more mature companies.

Many technical problems are unsolved or undersolved, and talented individuals can easily find large chunks of ownership with relatively little legacy debt and make a bit of an individual dent.

A high level of individual ownership leads to variations in engineering rigor across the org. It's the right thing not to try too hard to rein it in and stifle autonomy, but it can lead to frustrating experiences at times. Simply put, this is not a company where every candidate can succeed.

I recommend Databricks as a place to work, but for a large number of people, I find I have to qualify that recommendation.

Not a suitable company to coast. WLB is decent and better than at many of our peers, but falls far short of several popular alternatives with comparable or easier interviewing bars.

Databricks is less willing to give out higher titles to ICs or grant higher org sizes to managers than most of our peers. Projects are more likely to be understaffed.

Weak internal mobility stifles growth, especially for less assertive folks. Not a suitable company to be narrowly focused on one-dimensional output.

Compared to more metrics-driven companies, Databricks requires individuals to take broader ownership and is less equipped to reward narrow specialists or goal-seekers.

If the above does not dissuade you, then I think Databricks is one of the best companies to work for on the market.

Consider being more vigilant about counteracting local rather than global decision-making. This feels increasingly prevalent across teams and job functions, and I've not yet heard publicly that this is a problem we should confront.

Keep up the focus on business goals and avoid sliding into non-core distractions.

Invest more in the dogfooding experience, including incentivizing teams to use the product more and build out internal data ecosystems, as well as providing better internal user support.