Building a Self-Service Data Platform With a Small Data Team
Overview
Experience | In Person |
---|---|
Type | Breakout |
Track | Data Engineering and Streaming |
Industry | Retail and CPG - Food |
Technologies | Delta Lake, Databricks Workflows, Unity Catalog |
Skill Level | Beginner |
Duration | 40 min |
Discover how Dodo Brands, a global pizza and coffee business with over 1,200 retail locations and 40k employees, revolutionized their analytics infrastructure by creating a self-service data platform. This session explores the approach to empowering analysts, data scientists and ML engineers to independently build analytical pipelines with minimal involvement from data engineers.
By leveraging Databricks as the backbone of their platform, the team developed automated tools like a "job-generator" that uses Jinja templates to streamline the creation of data jobs.
This approach minimized manual coding and enabled non-data engineers to create over 1,420 data jobs — 90% of which were auto-generated by user configurations.
Supporting thousands of weekly active users via tools like Apache Superset.
This session provides actionable insights for organizations seeking to scale their analytics capabilities efficiently without expanding their data engineering teams.
Session Speakers
Evgenii Dobrynin
/Senior Data Engineer
Dodo Brands
Gleb Lesnikov
/Head of Architecture
Dodo Brands