Building a Self-Service Data Platform With a Small Data Team

Learn how to revolutionize analytics infrastructure by creating a self-service data platform that empowers analysts, data scientists, and ML engineers to independently build analytical pipelines with minimal data engineering involvement. Explore Dodo Brands' approach to scaling their analytics capabilities across over 1,200 retail locations and 40,000 employees using Databricks as their platform backbone. Discover how their team developed automated tools including a "job-generator" utilizing Jinja templates to streamline data job creation, enabling non-data engineers to generate over 1,420 data jobs with 90% being auto-generated through user configurations. Examine the implementation strategies that support thousands of weekly active users through tools like Apache Superset, and gain actionable insights for organizations seeking to efficiently scale their analytics capabilities without expanding their data engineering teams. Presented by Evgenii Dobrynin, Senior Data Engineer at Dodo Brands, and Gleb Lesnikov, Head of Architecture at Dodo Brands, this conference talk provides practical guidance for building scalable, self-service data platforms in resource-constrained environments.