Joshua Rogers

I’m a Staff Data Engineer with 9+ years of experience building scalable lakehouse, streaming, and cloud-native data platforms using Databricks, Spark, Kafka, Snowflake, Redshift, and AWS/Azure technologies. I focus on real-time pipelines, medallion architectures, and governed analytics that support personalization, healthcare interoperability, experimentation, and ML workloads at petabyte scale.

At Nike, I architected a Consumer 360 Personalization Lakehouse Platform unifying app, SNKRS, NRC, Nike.com, and partner telemetry into a centralized member intelligence platform processing 120M+ consumer interaction events daily. I led a real-time Personalization & Audience Feature Platform that reduced feature delivery latency from 4 hours to under 45 seconds, using Spark Structured Streaming, a Redis-backed Feature Store, and Delta Change Data Feed. I also built enterprise-scale Bronze/Silver/Gold medallion CDC ingestion pipelines across 40+ upstream systems, and delivered governed semantic marts enabling self-service analytics for 500+ global stakeholders.

I’ve strengthened reliability and governance through Unity Catalog, AWS Lake Formation, RBAC, OpenLineage integrations, and production engineering practices like Terraform-based IaC and CI/CD automation. At Optum, I modernized an Enterprise Healthcare Lakehouse Platform supporting 285M+ patient/member records, improving onboarding time for new clinical data domains by 60% and ingestion reliability to 99.9%. At Uber and Walmart, I delivered high-volume streaming and batch pipelines that improved freshness and performance, reduced incidents by 40%, and raised reliability—while partnering with ML teams to operationalize feature engineering and experimentation workflows.