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.
--- Databricks applicants
Please apply through our official Careers page at databricks.com/company/careers.
All official communication from Databricks will come from email addresses ending with @databricks.com or @goodtime.io (our meeting tool).
Rating Reviews
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Pros: The opportunity to work on truly groundbreaking technology in the data analytics and AI space is unmatched. I gained immense experience with distributed systems and cloud-native architectures. My colleagues were brilliant, driven, and always willing to share knowledge, which fostered a great sense of camaraderie. The remote work flexibility was also a huge plus, allowing for a good balance.
Cons: While career growth is abundant, it can sometimes feel like a sprint. There's a constant pressure to deliver at a high level, which occasionally impacts work-life balance, especially during critical project phases. Some internal processes could be streamlined to reduce overhead for engineers.
Advice to Management: Continue investing in mentorship programs to help newer engineers navigate the steep learning curve and maintain focus on scalable engineering processes.
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Pros: The caliber of people here is incredibly high; you're surrounded by brilliant minds. The opportunities for learning and contributing to cutting-edge big data solutions are immense. The company culture generally fosters collaboration and innovation. The hybrid work model in London offers good flexibility.
Cons: With rapid growth, processes can sometimes lag behind, leading to occasional inefficiencies. Communication across globally distributed teams can sometimes be a challenge, requiring extra effort to stay aligned. The pace can be demanding, impacting work-life balance during peak periods.
Advice to Management: Continue investing in tools and processes that support scalable growth and streamline cross-functional collaboration. Recognize and reward the efforts of teams managing the complexity of rapid expansion.
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Pros: The caliber of talent at Databricks is exceptional. You're constantly surrounded by brilliant minds working on solving complex problems in the data intelligence platform space. The remote and hybrid work flexibility is a major plus, and the impact of your work on the cloud data landscape is significant. Great career potential for motivated individuals.
Cons: While the culture is generally supportive, there are moments where communication across different global teams can feel a bit fragmented, leading to minor delays. Sometimes, rapid growth can mean processes aren't fully established, which can be a bit chaotic. Managing diverse global projects requires constant alignment.
Advice to Management: Continue fostering cross-team communication and knowledge sharing to streamline global project execution. Recognize and celebrate team wins more frequently.
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What's the onboarding process like for new data scientists at Databricks, especially for remote employees?
My onboarding at Databricks as a remote data scientist was really structured, with clear goals and regular check-ins. I felt supported from day one, which was great for getting up to speed quickly in the fast-paced big data industry.
What's the onboarding process like for new data engineers at Databricks?
My onboarding as a data engineer at Databricks was really structured, with clear goals and access to great resources. The team made sure I felt supported navigating the tools and company culture, even in a remote setup.
What kind of career growth can I expect at Databricks, especially coming from a data engineering background?
Databricks offers great visibility into diverse career paths; I've seen data engineers transition into machine learning engineering or even management roles within our large tech company.
As a CEO, how does Databricks' platform impact our long-term business outlook in the AI industry?
Databricks' unified approach to data and AI, especially for enterprise-level companies, has really streamlined our operations, giving us a clearer vision for future growth and innovation.
What's it like working in category management at Databricks, especially for someone focused on performance marketing?
In category management at Databricks, I found my performance marketing focus was well-supported; we used the platform extensively to analyze campaign effectiveness and drive data-informed decisions for key verticals.
What's the dress code for remote meetings at Databricks?
For remote meetings at Databricks, the dress code is business casual, though most engineers and data scientists opt for comfortable, professional attire. It's generally relaxed, focusing on looking presentable on camera for internal and client interactions across our global offices.
As a category manager at a mid-sized retail company in Chicago, how has Databricks helped with change management for new data initiatives?
Databricks has been instrumental in our change management process; it unified our data teams and streamlined how we roll out new analytics projects for category management, making adoption smoother across our retail operations.
Does Databricks offer fully remote roles for data scientists in the UK, or is it a hybrid model?
Databricks supports remote work for many roles, including data scientists, and they have a global presence. While some roles are fully remote, others might be hybrid depending on the team and location, so it's best to check the specific job posting.
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