P-1348
At Databricks, we are passionate about enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Our engineering teams build technical products that fulfill real, important needs in the world. We always push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is important to making customers successful on our platform.
We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above.
As a Senior Software Engineer working on the Data Platform team you will help build the Data Intelligence Platform for Databricks that will allow us to automate decision-making across the entire company. You will achieve this in collaboration with Databricks Product Teams, Data Science, Applied AI and many more. You will develop a variety of tools spanning logging, orchestration, data transformation, metric store, governance platforms, data consumption layers etc. You will do this using the latest, bleeding-edge Databricks product and other tools in the data ecosystem - the team also functions as a large, production, in-house customer that dog foods Databricks and guides the future direction of the product.
The impact you will have:
- Design and run the Databricks metrics store that enables all business units and engineering teams to bring their detailed metrics into a common platform for sharing and aggregation, with high quality, introspection ability and query performance.
- Design and run the cross-company Data Intelligence Platform, which contains every business and product metric used to run Databricks. You’ll play a key role in developing the right balance of data protections and ease of shareability for the Data Intelligence Platform as we transition to a public company.
- Develop tooling and infrastructure to efficiently manage and run Databricks on Databricks at scale, across multiple clouds, geographies and deployment types. This includes CI/CD processes, test frameworks for pipelines and data quality, and infrastructure-as-code tooling.
- Design the base ETL framework used by all pipelines developed at the company.
- Partner with our engineering teams to provide leadership in developing the long-term vision and requirements for the Databricks product.
- Build reliable data pipelines and solve data problems using Databricks, our partner’s products and other OSS tools. Provide early feedback on the design and operations of these products.
- Establish conventions and create new APIs for telemetry, debug, feature and audit event log data, and evolve them as the product and underlying services change.
- Represent Databricks at academic and industrial conferences & events.
What we look for:
- 6+ years of industry experience
- 4+ years of experience providing technical leadership on large projects similar to the ones described above - ETL frameworks, metrics stores, infrastructure management, data security.
- Experience building, shipping and operating reliable multi-geo data pipelines at scale.
- Experience working with and operating workflow or orchestration frameworks, including open source tools like Airflow and DBT or commercial enterprise tools.
- Experience with large-scale messaging systems like Kafka or RabbitMQ or commercial systems.
- Excellent cross-functional and communication skills, consensus builder.
- Passion for data infrastructure and for enabling others by making their data easier to access.
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.
Skills Required
- 6+ years of industry experience
- 4+ years providing technical leadership on large projects (ETL frameworks, metrics stores, infrastructure management, data security)
- Experience building, shipping, and operating reliable multi-geo data pipelines at scale
- Experience with workflow/orchestration frameworks (e.g., Airflow, DBT) or enterprise equivalents
- Experience with large-scale messaging systems (e.g., Kafka, RabbitMQ) or commercial equivalents
- Experience developing CI/CD processes, test frameworks for pipelines and data quality, and infrastructure-as-code tooling
- Experience designing and running metrics stores and ETL frameworks used company-wide
- Excellent cross-functional communication and consensus-building skills
- Passion for data infrastructure and enabling easier data access
Databricks Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Databricks and has not been reviewed or approved by Databricks.
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Healthcare Strength — Company materials highlight comprehensive medical, dental, and vision coverage alongside mental-health resources, wellness reimbursements, and business travel insurance. Offerings are described as broad and modern, with core health coverage consistently emphasized.
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Parental & Family Support — Paid parental leave is explicitly called out, with details such as up to 20 weeks for birthing parents and up to 12 weeks for non-birthing parents in the U.S. Public materials also reference family-forming support, reinforcing the focus on families.
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Wellbeing & Lifestyle Benefits — Wellness programs and perks include gym reimbursement, periodic wellness events (e.g., yoga, massages), and in-office meals and snacks in many locations. Personal development funds and discounts further enhance lifestyle and growth support.
Databricks Insights
What We Do
As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.
