Enterprise Data Platform
Scale a data platform to handle 6B+ rows daily while maintaining reliability and performance for analytics teams across the organization.
Stack
Approach
Built internal tooling for the analytics team, focusing on data pipeline reliability and developer experience. Improved query performance, streamlined ETL processes, and introduced monitoring to catch failures before they impacted downstream consumers.
Results
Data platform processing 6B+ rows daily with improved reliability, powering analytics and business intelligence across the organization.
Under the Hood
Worked within a large-scale Rails monolith backed by PostgreSQL, Redis, and Sidekiq. Focused on optimizing long-running background jobs, improving database query patterns at scale, and building internal tools that reduced manual toil for the data team.