Session
Federated Data Pipelines
Overview
Experience | In Person |
---|---|
Type | Breakout |
Track | Data Engineering and Streaming |
Industry | Enterprise Technology, Professional Services |
Technologies | Apache Spark, Databricks SQL |
Skill Level | Intermediate |
Duration | 40 min |
Are you struggling to keep up with rapid business changes that demand constant updates to your data pipelines? Is your data engineering team growing rapidly just to manage this complexity? Databricks was not immune to this challenge either. Managing our BI with contributions from hundreds of Product Engineering Teams across the company while maintaining central oversight and quality posed significant hurdles. Join us to learn how we developed a config-driven data pipeline framework using Metric Store and UC Metrics that helped us reduce engineering effort — achieving the work of 100 classical data engineers with just two platform engineers.
Session Speakers
Neo Ni
/Senior Software Engineer
Databricks
Rohit Mathews
/Senior Software Engineer
Databricks