Staff Software Engineer - Multi Cloud Efficiency
Databricks is hiring a Staff Software Engineer - Multi Cloud Efficiency in Bengaluru, India. Level rates it ; you can apply on Databricks.
Level's read on this job
- Level rates this software engineer role Little AI ●○○○: aI is not part of the work.
- Tools and skills the posting cites include AWS, Azure and Google Cloud.
- Level classifies it as a lead role.
- Level lists 900 other open roles at Databricks.
AI in this role
Serve as technical lead for multi-cloud efficiency, architecting large-scale cost optimization and automation systems.
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 aren't just cutting costs; we are engineering systems to scale efficiently as our cloud footprint expands into the hundreds of millions of dollars.
The Role
As a Staff Software Engineer, you will serve as the technical lead for the Bengaluru MCE chapter. You will be responsible for defining the technical strategy for efficiency projects where the solutions are not yet known. You will lead cross-functional efforts, working with finance and cost team, to tackle massive-scale engineering challenges, ensuring our systems can automatically drive cost efficiency and handle the complexity of global, multi-cloud data processing without compromising on performance or stability. As one of the founding senior engineers of the Bengaluru MCE chapter — a team that has already delivered millions of dollars in verified annual cloud savings within two quarters of formation — you will shape its technical direction and help scale it toward amplifying global impact.
The impact you will have
- Architect at Scale: Lead the design and implementation of systems to optimize cloud spend, driving impact in the magnitude of hundreds of millions of dollars. You will architect solutions for complex problems like reserved-instance automation, tag-based cost attribution at scale, automated waste-cleanup policy engines, and cross-cloud resource governance.
- Drive Technical Strategy: Identify and deliver high-impact, well-adopted projects that solve complex efficiency problems. You will define the roadmap for our efficiency pillar, conducting thorough design reviews and risk assessments for systems supporting the company's core infrastructure.
- Engineer for Efficiency: Design scalable systems for regression detection and automated resource rightsizing. You will build the frameworks that allow product teams to measure their "efficiency footprint” — the cost and resource impact of their services and hold them accountable through automated release gates that block changes that regress agreed efficiency targets (SLOs).
- Operational Excellence: Serve as a technical authority for incident management, addressing complex, system-wide performance issues. You will improve the stability and reliability of our internal platform tools, ensuring they are robust enough to manage our growing global scale.
- Technical Leadership: Act as a force multiplier by mentoring junior and senior engineers, raising the bar for engineering quality, and driving engineering culture across the organization.
- Build self-driving efficiency systems: Design the automation and agentic layers — AI-driven detection, decisioning, and autonomous remediation — that let cost governance run continuously at scale, shifting the team from manual cleanup to systems that keep themselves efficient.
What We Look For
- 9+ years of experience building production-grade, distributed systems in Java, Scala, C++, or Go.
- Proven track record of architecting solutions for large-scale infrastructure, cloud computing (AWS/Azure/GCP), and container orchestration (Kubernetes/Docker).
- Deep expertise in identifying and solving performance bottlenecks in high-throughput, distributed environments.
- Demonstrated ability to drive technical requirements for ambiguous problems where the path forward is not obvious.
- T-shaped engineering skills: depth in distributed systems and breadth across cloud infrastructure, monitoring, and software lifecycles.
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.
How we rate this
Staff Software Engineer - Multi Cloud Efficiency at Databricks rates 10 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in software engineer jobs at this level
Pay
- Typical software engineer job
- $167k
This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs
Questions you could be asked
- Tell me about a project where backend was part of your work. What did you do?
- Tell me about a project where cloud infrastructure was part of your work. What did you do?
- Tell me about a project where system design was part of your work. What did you do?
- Tell me about a project where cost optimization was part of your work. What did you do?
- Tell me about a project where technical leadership was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Backend, Cloud Infrastructure, System Design, Cost Optimization, and Technical Leadership. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
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