At Databricks, we are building and running the world's best data and AI infrastructure platform. Our engineering teams build technical products that fulfill real, important needs in the world. 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.
\nAs 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.
\nThe impact you will have:
\nXML job scraping automation by YubHub
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\nThe impact you will have includes designing and running the Databricks metrics store, cross-company Data Intelligence Platform, and developing tooling and infrastructure to efficiently manage and run Databricks at scale. You will also design the base ETL framework used by all pipelines developed at the company, partner with engineering teams to provide leadership in developing the long-term vision and requirements for the Databricks product, and establish conventions and create new APIs for telemetry, debug, feature, and audit event log data.
\nTo be successful in this role, you will need 12+ years of industry experience, 4+ years of experience building large-scale distributed systems, and 5+ years of providing technical leadership on large projects similar to the ones described above. You will also need experience with ETL frameworks, metrics stores, infrastructure management, data security, and experience building, shipping, and operating reliable multi-geo data pipelines at scale.
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