Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and over 60% of the Fortune 500 — rely on Databricks to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified Data Intelligence Platform that includes Agent Bricks, Lakeflow, Lakehouse, Lakebase and Unity Catalog.
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Rating Reviews
Rating is calculated based on
21
reviews and is evolving.
Pros: I really appreciate the remote work setup here. It's a huge plus for work-life balance, helps with personal stuff around my data engineering tasks. For big tech, the flexibility to work from home most days is great.
Cons: Sometimes meetings get stacked across time zones, which can be tough. There's an expectation to be online and responsive, so 'unplugged' flexibility isn't always there. It's not a 40-hour week every time, especially around deadlines.
Advice to Management: Try to consolidate meetings across time zones better. Encourage managers to really let people disconnect when not actively working.
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Pros: The base salary for a Software Engineer here is really competitive, especially for a big tech company. The stock grants (RSUs) are also quite generous and a major part of total compensation. We've got a decent medical plan too, which is a big plus.
Cons: The RSU vesting schedule can feel a bit slow, especially early on. Also, the annual bonus isn't always as high as I'd hope, and raises sometimes feel modest compared to how much we contribute.
Advice to Management: Re-evaluate the RSU vesting acceleration for long-term employees and ensure annual bonus targets are more consistently met for engineers working on the data science platform.
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Pros: The base salary is really strong for a Senior Software Engineer, especially when you're working remote. Stock options at this data and AI company have definitely been good. Health insurance and 401k match are pretty standard, but solid.
Cons: Bonuses aren't always clear or consistent, which can be frustrating for software development roles. It feels like some benefits are lagging compared to other big tech firms in the Bay Area. Also, the equity refreshers aren't as generous as I hoped after a year or two.
Advice to Management: Improve transparency around bonus structures and make equity refreshers more competitive with other top-tier data companies.
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What's the day-to-day environment like for a software engineer at Databricks, especially regarding collaboration and innovation?
Engineers at Databricks typically work in a fast-paced, collaborative environment focused on tackling complex data challenges. You'll find a strong emphasis on open communication and knowledge sharing, with opportunities to contribute to cutting-edge projects in the big data and AI space.
What is Databricks' policy on remote work for software engineers in the Bay Area?
No answers yet.
How does Databricks approach remote work and hybrid models for their software engineering roles, and how does it impact team collaboration?
No answers yet.
What is Databricks' policy on remote work for software engineers in the US, and how does it impact team collaboration?
No answers yet.
What is the management style like at Databricks, particularly for data engineers in the San Francisco Bay Area?
Management at Databricks generally focuses on empowering engineers and fostering a collaborative environment. Expect regular check-ins and a focus on impact, with opportunities to contribute to significant projects in the fast-paced big data industry.
What is the general working culture like for software engineers at Databricks, especially regarding collaboration and innovation?
The culture at Databricks fosters a highly collaborative environment where engineers are encouraged to share ideas and contribute to innovative projects. Teamwork is central, with cross-functional teams frequently working together on complex data and AI solutions.
What is the day-to-day work environment like for a software engineer at Databricks, especially regarding collaboration?
Engineers at Databricks typically work in a collaborative environment, often using agile methodologies. Expect regular team meetings, code reviews, and cross-functional discussions, especially within the data and AI platform development teams.
What is the typical interview process like for an engineering role at Databricks, and how long does it usually take?
The Databricks interview process for engineering candidates typically involves an initial recruiter screen, followed by technical phone interviews, and then on-site (or virtual) interviews. The entire process can take anywhere from 2 to 4 weeks to complete, depending on scheduling.
