We’re excited to announce that Databricks was named one of many 2024 Fortune Finest Workplaces in Know-how™. This award displays our dedication to creating an surroundings the place Bricksters can thrive and innovate whereas serving to information groups clear up the world’s hardest issues. Rooted in our origins on the UC Berkeley AMP Analysis Lab, Databricks is devoted to cultivating an open and clear tradition, driving the subsequent technology of knowledge intelligence, and shaping the way forward for information and AI.
The Finest Workplaces in Know-how record is extremely aggressive. Nice Place To Work, the worldwide authority on office tradition, conducts America’s largest ongoing annual workforce research, primarily based on over 1.3 million survey responses and information from corporations representing greater than 8.2 million workers this 12 months alone.
Don’t simply take their phrase for it. Hear immediately from the Bricksters who make Databricks a Finest Office in Know-how.
A Tradition of Information-Pushed Engineering
Shoumik Palkar, Sr. Workers Software program Engineer
I work at Databricks right now for a similar causes I joined the corporate almost 5 years in the past: the breadth of expertise throughout the engineering group, the breakneck tempo of innovation and studying, and the deep worth positioned on utilizing data-driven choices to make our product higher for our prospects. The three are intrinsically related, with the fountainhead being the energy of the engineering workforce. Our engineers—who carry a long time of expertise from the world’s largest information techniques of their previous lives—function in an area the place “cutting-edge” evolves week-over-week and steady studying turns into a necessity, whether or not it’s by maintaining with the newest tutorial convention proceedings or by way of cross-team collaborations to seek out novel options.
However, instinct and studying usually are not sufficient. On the middle of every resolution at Databricks is the info itself. Information is the good equalizer, offering a unified language that enables us to push for innovation throughout the product with confidence. These elements make Databricks an extremely rewarding place to work, each by fostering private development by way of mentorship by world-class specialists and by enabling people in any respect ranges to ship buyer worth by letting the info determine.
Analysis-Pushed Tasks
Jonathan Ellithorpe, Workers Software program Engineer
Databricks’ first-principles strategy to engineering empowers me to dig deep and clear up issues at their core. On my workforce we construct the basic distributed techniques “constructing blocks” that assist companies to function effectively and reliably at scale, together with high-performance storage, distributed caching, low-latency cache invalidation, and dynamic sharding and cargo balancing. We additionally work intently with groups throughout the corporate to get deep into their code and architectures to uncover widespread patterns and determine the place new abstractions are wanted. Due to Databricks’ data-driven and extremely collaborative tradition, it’s simple for us to take a research-style strategy to our work the place we favor early experimentation and measurement to check hypotheses and leverage prototyping and a build-then-iterate course of to innovate rapidly.
Moreover addressing challenges in our infrastructure utilizing a first-principles mindset, steady studying {and professional} development can also be a key a part of my expertise at Databricks. With the corporate’s tutorial roots and dedication to publishing recurrently, I’m always inspired not solely to develop my data and expertise but additionally to be a part of the bigger tutorial group. For instance, Databricks has sponsored my attendance at OSDI annually since I joined, which has been important for me to remain related to the group and hold abreast of the newest within the discipline, together with in essential new areas such because the intersection of ML and techniques. Publishing can also be extremely inspired, and this 12 months we submitted a place paper on high-performance in-memory stateful companies, showing at HPTS 2024.
In my view, the mixture of a first-principles-based strategy to engineering, a data-driven tradition, and an emphasis on steady private development and growth signifies that at Databricks, there’s actually no restrict to what you are able to do.
Distinctive and Vibrant Tradition
Tao Tao, Director, Engineering
Databricks stands out with its distinctive energy of bringing collectively the most effective of the business, the open supply group, and tutorial analysis. We created an entire new normal of “good engineering” that’s visionary, elegant, and sensible. At our core, our inclusive and collaborative tradition fosters a seamless alternate of concepts and experience throughout groups and disciplines.
This cross-team synergy is a core driver of our innovation. My latest instance of this spirit is the event of our newest Lakehouse Collaboration product providing: Databricks Clear Rooms – a privacy-safe resolution for safe information collaboration powered by Delta Sharing. This breakthrough emerged from the shut teamwork among the many business specialists, partnership workforce, belief and security specialists, and a number of engineering groups throughout the stack at Databricks. By harnessing various views and specialised data, the workforce was capable of design an answer that not solely addresses the present complicated challenges however can also be future-proofing for upcoming AI workloads.
For many who search to hitch a dynamic and inclusive workforce alongside world-class specialists and to make tangible impacts on the info and AI business, Databricks affords an distinctive alternative.
A Accountable Method to AI: Jasmine Collins, Analysis Scientist, Mosaic AI
At Databricks, we prioritize the creation of protected and accountable AI techniques that greatest swimsuit buyer wants. A latest instance of this dedication is the ImageAI mannequin, collectively skilled with Shutterstock for producing photos tailor-made to enterprise use instances.
Not like most present picture technology fashions skilled on arbitrary web-scraped photos and captions, we took a extra accountable and thoroughly curated strategy. By coaching our mannequin from scratch on Shutterstock’s proprietary and vetted picture repository, the mannequin’s outputs usually are not solely commercially viable however may be trusted for a variety of functions. By utilizing a well-governed dataset, we make sure that the mannequin’s capabilities and limitations are clearly understood, making it extra appropriate for its supposed use instances in enterprise environments.
This strategy highlights our broader dedication to accountable AI growth throughout all of our initiatives. By prioritizing information high quality, investigating dataset bias, and making certain transparency, we goal to create protected and dependable AI techniques.
Construct the way forward for open supply AI-driven information intelligence. Be part of us!
Be taught extra about profession alternatives at Databricks and see present job openings.