Synced from Greenhouse · Jul 1

Software Engineer

DatabricksBengaluru, IndiaPosted Jul 1, 2026
Software EngineerSenior
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Jul 1
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Greenhouse
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Job descriptionReq 7654347002

P-1346

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. Databricks Mosaic AI offers a unique data-centric approach to building enterprise-quality, Machine Learning and Generative AI solutions, enabling organizations to securely and cost-effectively own and host ML and Generative AI models, augmented or trained with their enterprise data. 

The Money team's mission at Databricks is to maximize the value that our customers derive from their investments in data projects. We accomplish this through innovative commercialization strategies, timely & accurate billing,  cost optimization tools, intelligent resource usage controls, and cutting-edge engineering. We provide a seamless and consistent experience set of platforms for all Databricks products to reach customers.

As one of the first engineers for Money at Databricks India, you will be key to building a base for one of Databricks’ most central engineering teams. You will own critical components that form the backbone of our products, starting with Databricks’ resource admission control and usage governance infrastructure. Your role is crucial in helping bring diverse business needs together, including abuse prevention, product commercialization motions, and reliable product availability at scale. You will work closely with infrastructure as well as product teams in bringing critical governance functionality to Databricks customers.

The impact you will have:

  • Own Money systems and services that govern usage of all Databricks products and offerings.
  • Enhance engineering and infrastructure efficiency, reliability, accuracy, and response times, including CI/CD processes, test frameworks, data quality assurance, end-to-end reconciliation, and anomaly detection.
  • Collaborate with platform and product teams to develop and implement innovative infrastructure that scales to meet evolving needs.
  • Contribute to long-term vision and requirements development for Databricks products, in partnership with our engineering teams.

What we look for:

  • BS (or higher) in Computer Science, or a related field
  • 7+ years of production level experience in one of: Java, Scala, C++, or similar language
  • Comfortable working towards a multi-quarter vision with incremental deliverables
  • Proven track record in architecting, developing, deploying, and operating components of large scale distributed systems
  • Experience with software security and systems that handle sensitive data
  • Demonstrated ability to lead engineering projects across functional and organizational boundaries
  • A proactive approach and a passion for delivering high-quality solutions
  • Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, Kubernetes

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform 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 platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.

Benefits

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

View original posting on Greenhouse

What applying to Databricks usually looks like

Based on publicly available information, candidates applying through greenhouse for roles at Databricks can generally expect a structured process typical of this ATS. This commonly begins with an online application and resume screen, followed by a recruiter conversation to discuss background and role fit. Depending on the position, candidates may encounter technical assessments, take-home exercises, or case studies, particularly for engineering, data, and analytical roles. The process may include multiple stages such as hiring manager conversations, panel discussions, and team or cross-functional interviews. Response times vary and communication is typically managed through the greenhouse platform, including scheduling and status updates. Candidates should prepare to discuss relevant experience, technical skills, and role-specific scenarios, as greenhouse-based processes commonly emphasize structured evaluation criteria across candidates to support consistent, comparative hiring decisions throughout the pipeline.

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