Synced from Greenhouse · Jul 1

Software Engineer

DatabricksBengaluru, IndiaPosted Jul 1, 2026
Software EngineerSenior
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Jul 1
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Job descriptionReq 8602402002

P-1563

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. And we're only getting started in Bengaluru , India ! As a software engineer with a backend focus, you will work with your team to build infrastructure for the Databricks platform at scale.

About the Team

We manage the infrastructure efficiency for one of the world's largest data and AI platforms. Operating at massive scale across AWS, Azure, and GCP, our mission is to ensure that every dollar spent on cloud infrastructure is optimized. The MCE team builds the critical tools, frameworks, and automated systems that provide deep cost visibility and ensure maximum resource utilization. We are looking for engineers to help us engineer systems that optimize our footprint as we scale into the hundreds of millions of dollars in cloud spend.

The Role

As a Senior Software Engineer, you will own the end-to-end design and delivery of high-impact engineering projects. You will act as a primary owner of key system components, handling technical ambiguity, collaborating with stakeholders, and delivering robust, scalable solutions. Your work will directly impact our infrastructure margins by building the next generation of cost attribution, automated resource management, and efficiency tooling.

The impact you will have

  • End-to-End System Design: Lead projects from concept to deployment. You will design and build scalable systems that handle high-volume data streams to provide accurate cost attribution and resource management, turning chaotic cloud spend into actionable data.
  • Scaling & Optimization: Identify and eliminate inefficiencies in our cloud architecture. You will engineer solutions that mitigate resource waste, improve attribution accuracy, and raise the efficiency of our underlying cloud and data infrastructure.
  • Component Ownership: Act as the technical expert for your service area. You will take ownership of the full lifecycle of your services, ensuring high code quality, effective monitoring, and low operational overhead.
  • Bridge the Gap: Work effectively with product and infrastructure teams to turn business needs into technical specifications. You will develop tooling that simplifies the complex world of cloud economics for other engineers and budget owners.
  • Mentorship & Best Practices: Uplevel the team by contributing to code reviews, sharing engineering best practices, and mentoring junior engineers. You will drive a shift-left culture — catching cost and efficiency problems early in the development cycle — by integrating efficiency checks directly into the developer workflow.
  • Automate the manual: Build the automation and AI/agentic tooling that detects waste, attributes cost, and remediates issues with minimal human intervention — turning repetitive cost operations into self-running systems.

What We Look For

  • 6+ years of experience, including producing high-quality production code and detailed technical design documents for distributed systems.
  • Proven ability to break down complex, multi-month projects into actionable milestones and tasks.
  • Solid grasp of industry best practices for distributed systems (monitoring, documentation, testing, and "fit and finish").
  • Experience in optimizing cloud resource utilization or developing large-scale distributed tools.
  • Ability to make well-reasoned trade-offs between system performance, development velocity, and technical debt.

 

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.

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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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Software Engineer
Databricks · Bengaluru, India
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