2024 Fortune Best Workplaces in Technology™ recognizes Databricks

We are excited to announce that Databricks was named one of the 2024 Fortune Best Workplaces in Technology™. This award reflects our commitment to creating an environment where Bricksters can thrive and innovate while helping data teams solve the world’s toughest problems. Rooted in our origins at the UC Berkeley AMP Research Lab, Databricks is dedicated to cultivating an open and transparent culture, driving the next generation of data intelligence, and shaping the future of data and AI.

The Best Workplaces in Technology list is highly competitive. Great Place To Work, the global authority on workplace culture, conducts America’s largest ongoing annual workforce study, based on over 1.3 million survey responses and data from companies representing more than 8.2 million employees this year alone.

Don’t just take their word for it. Hear directly from the Bricksters who make Databricks a Best Workplace in Technology.

A Culture of Data-Driven Engineering

Shoumik Palkar, Sr. Staff Software Engineer

I work at Databricks today for the same reasons I joined the company nearly five years ago: the breadth of experience within the engineering organization, the breakneck pace of innovation and learning, and the deep value placed on using data-driven decisions to make our product better for our customers. The three are intrinsically connected, with the fountainhead being the strength of the engineering team. Our engineers—who bring decades of experience from the world’s largest data systems in their past lives—operate in a space where “cutting-edge” evolves week-over-week and continuous learning becomes a necessity, whether it is by keeping up with the latest academic conference proceedings or through cross-team collaborations to find novel solutions.

Nevertheless, intuition and learning are not enough. At the center of each decision at Databricks is the data itself. Data is the great equalizer, providing a unified language that allows us to push for innovation across the product with confidence. These ingredients make Databricks an incredibly rewarding place to work, both by fostering personal growth through mentorship by world-class experts and by enabling individuals at all levels to deliver customer value by letting the data decide.

Research-Driven Projects

Jonathan Ellithorpe, Staff Software Engineer

Databricks’ first-principles approach to engineering empowers me to dig deep and solve problems at their core. On my team we build the fundamental distributed systems “building blocks” that help services to operate efficiently and reliably at scale, including high-performance storage, distributed caching, low-latency cache invalidation, and dynamic sharding and load balancing. We also work closely with teams across the company to get deep into their code and architectures to uncover common patterns and identify where new abstractions are needed. Thanks to Databricks’ data-driven and highly collaborative culture, it’s easy for us to take a research-style approach to our work where we favor early experimentation and measurement to test hypotheses and leverage prototyping and a build-then-iterate process to innovate quickly.

Besides addressing challenges in our infrastructure using a first-principles mindset, continuous learning and professional growth is also a key part of my experience at Databricks. With the company’s academic roots and commitment to publishing regularly, I am constantly encouraged not only to expand my knowledge and skills but also to be part of the larger academic community. For example, Databricks has sponsored my attendance at OSDI each year since I joined, which has been essential for me to stay connected to the community and keep abreast of the latest in the field, including in important new areas such as the intersection of ML and systems. Publishing is also highly encouraged, and this year we submitted a position paper on high-performance in-memory stateful services, appearing at HPTS 2024.

In my opinion, the combination of a first-principles-based approach to engineering, a data-driven culture, and an emphasis on continuous personal growth and development means that at Databricks, there’s really no limit to what you can do.

Unique and Vibrant Culture

Tao Tao, Director, Engineering

Databricks stands out with its unique strength of bringing together the best of the industry, the open source community, and academic research. We created a whole new standard of “good engineering” that is visionary, elegant, and practical. At our core, our inclusive and collaborative culture fosters a seamless exchange of ideas and expertise across teams and disciplines.

This cross-team synergy is a core driver of our innovation. My recent example of this spirit is the development of our latest Lakehouse Collaboration product offering: Databricks Clean Rooms - a privacy-safe solution for secure data collaboration powered by Delta Sharing. This breakthrough emerged from the close teamwork among the industry experts, partnership team, trust and safety specialists, and multiple engineering teams across the stack at Databricks. By harnessing diverse perspectives and specialized knowledge, the team was able to design a solution that not only addresses the current complex challenges but is also future-proofing for upcoming AI workloads.

For those who seek to join a dynamic and inclusive team alongside world-class experts and to make tangible impacts on the data and AI industry, Databricks offers an exceptional opportunity.

A Responsible Approach to AI

Jasmine Collins, Research Scientist, Mosaic AI

At Databricks, we prioritize the creation of safe and responsible AI systems that best suit customer needs. A recent example of this commitment is the ImageAI model, jointly trained with Shutterstock for generating images tailored to enterprise use cases.

Unlike most existing image generation models trained on arbitrary web-scraped images and captions, we took a more responsible and carefully curated approach. By training our model from scratch on Shutterstock's proprietary and vetted image repository, the model’s outputs are not only commercially viable but can be trusted for a wide range of applications. By using a well-governed dataset, we ensure that the model's capabilities and limitations are clearly understood, making it more suitable for its intended use cases in enterprise environments.

This approach highlights our broader commitment to responsible AI development across all of our initiatives. By prioritizing data quality, investigating dataset bias, and ensuring transparency, we aim to create safe and reliable AI systems.

Build the future of open source AI-driven data intelligence. Join us!

Learn more about career opportunities at Databricks and see current job openings.