Strategic Overview
Senior Software Engineer - Data + AI Observability at Databricks is a dev opportunity centered on the specialist responsibilities and outcomes described in the employer's listing.
The published role emphasizes work such as Develop systems that make it simple for customers to answer questions about their Databricks environment by providing a reliable and timely interface for observability Effectively lead large milestones from the observability roadmap, contribute to the….
The role is listed for Bengaluru, India with the working arrangement published with the role, giving candidates the practical context needed to assess fit before applying.
Key information at a glance
About This Role
P-1385
Companies are investing billions of dollars into developing and deploying AI and the data platforms that enable it. But do they know what is happening?
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 —…
Key Responsibilities & Objectives
- Develop systems that make it simple for customers to answer questions about their Databricks environment by providing a reliable and timely interface for observability
- Effectively lead large milestones from the observability roadmap, contribute to the long-term vision and requirements development for Databricks products
- Mentor other engineers towards contributing to the product and their career growth
- Drive integration with popular tools and services in the broader data warehousing ecosystem
Required Qualifications & Candidate Blueprint
- 6+ years of production level experience in one of: Java, Scala, Python, C++, or similar language
- Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, Kubernetes
- Proven track record in architecting, developing, deploying, and operating components of large scale distributed systems
Salary & Benefits
The available source data does not publish a numerical salary range for this opening. We do not estimate or substitute third-party figures.
- Effectively lead large milestones from the observability roadmap, contribute to the long-term vision and requirements development for Databricks products
Full Job Description
The following is the complete job description supplied by the source. We sanitize unsafe markup and remove external links, but do not shorten or rewrite the employer's source content.
P-1385
Companies are investing billions of dollars into developing and deploying AI and the data platforms that enable it. But do they know what is happening?
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 tackle 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.
As a Senior Software Engineer on the Customer Foresight Team, you'll lead the development of products that customers use to get insights on their AI and data workloads, optimize their performance, and lower costs. You will build data infrastructure that processes billions of entries daily, deploy to over 65 cloud regions worldwide, and enable some of the world's biggest companies to conduct their DevOps, FinOps, SecOps and AIOps jobs.
This role requires leading the technical development of product milestones from refinement of requirements, through execution, operation, and iterating with the broader product development team and partner teams to ensure product success.
The impact you will have:
- Develop systems that make it simple for customers to answer questions about their Databricks environment by providing a reliable and timely interface for observability
- Make it easy for frameworks teams across Databricks to publish their data to customers
- Effectively lead large milestones from the observability roadmap, contribute to the long-term vision and requirements development for Databricks products
- Mentor other engineers towards contributing to the product and their career growth
- Optimize the scalability and cost of large data pipelines towards reducing costs for customers and opening up new product opportunities
- Drive integration with popular tools and services in the broader data warehousing ecosystem
What we look for:
- 6+ years of production level experience in one of: Java, Scala, Python, C++, or similar language
- Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, Kubernetes
- Proven track record in architecting, developing, deploying, and operating components of large scale distributed systems
- Strong software engineering maturity: security, correctness, engineering excellence, operational excellence
- Platform mindset: effective building platforms for other software teams, iterating quickly to reduce friction to adoption, advocating for platform use
- Cross-functional skills: we have platform customers internal at Databricks as well as external customers, which requires strong cross-functional skills
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.
Editor’s Market Perspective (Our Custom Analysis)
Why This Position Matters
This dev opening is a useful opportunity for candidates whose experience matches the role-specific capabilities named in the listing. Its strongest career signal is the scope of the work itself — particularly Develop systems that make it simple for customers to answer questions about their Databricks environment by providing a reliable and timely interface for observability — rather than a generic title alone.
Resume & Application Strategy
For the application, mirror the employer's language where it truthfully matches your background: foreground the role-specific capabilities named in the listing, quantify outcomes from comparable work, and place the most relevant experience near the top of the resume. If the listing specifies tools, platforms, leadership scope, or domain experience, use those exact terms in context instead of presenting an unrelated keyword list.
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