FanDuel’s Data Challenges Before Snowplow + AWS | ETL Latency, Schema Management & Cost Scaling

Before adopting Snowplow and AWS, FanDuel faced major challenges with their behavioral data pipelines:

✅ Complex, custom ETL/ELT pipelines added latency and slowed access to insights

✅ Data wasn’t landing directly in the warehouse, creating engineering overhead

✅ Schema changes across decentralized teams caused friction for analysts

✅ Scaling event collection drove up infrastructure and cost concerns

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In this clip, Tony Cui (Senior Data Engineering Manager at FanDuel) explains what their “previous state” looked like—and why they turned to Snowplow + AWS to modernize their data infrastructure.

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👉 Watch the full 30-minute fireside chat with FanDuel, Snowplow, and AWS here:

https://snowplow.io/events/real-time-wins-how-fanduel-transforms-player-experience-with-aws-and-snowplow

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#FanDuel #Snowplow #AWS #DataEngineering #RealTimeData #ETL #DataPipelines #BehavioralData #AnalyticsEngineering #DataWarehouse