Have you ever wondered how a data company does data? In this session, Isaac Obezo, Staff Data Engineer at Starburst, will take you for a peek behind the curtain into Starburst’s own data architecture built to support batch processing of telemetry data within Galaxy data pipelines. Isaac will walk you through our architecture utilizing tools like git, dbt, and Starburst Galaxy to create a CI/CD process allowing our data engineering team to iterate quickly to deploy new models, develop and land data, and create and improve existing models in the data lake. Isaac will also discuss Starburst’s mentality toward data quality, the use of data products, and the process toward delivering quality analytics.
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Isaac Obezo
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Isaac Obezo is a Staff Data Engineer at Starburst Data. A seasoned software and data engineer, Isaac has worked at many different companies with the majority of his work revolving around “pushing data to some BI layer”. This included building out web apps, robots that tested attenuation (with EE), pythonic pipelines, and more. Most recently he helped build data to a single cloud based warehouse, and shortly after spent more time trying to decouple. Isaac lives in Seattle and in Isaac’s free time he finds himself making blacksmithing, gardening, or just riding around Seattle aimlessly on his bicycle.
Bio from: Data Universe 2024
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