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 .
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
Задачи
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
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
Требования
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
Условия
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees
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