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 Staff 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:

• 12+ years of industry experience 
• 4+ years of experience building large scale distributed systems
• 5+ 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.