Data, platform, ai.

• Migrating legacy redshift warehouse to databricks, consolidating pipelines, cutting costs, unlocking ml workloads.

• Giving ai engs the dopamine hit of "fresh" model features instead of "whenever batch god wills it".

Data platform.

• Enabled growth engs to launch personalized flows; cut event latency 95%+ so ops could react while users were still awake.

• Ported 100+ key dbt models to new cloud-native ELT, slashed incident downtime from 7d to 8h; established multi-vendor patterns (bc vendor lock-in sucks).

Data science & analytics.

• First data engineering hire; stood up full-stack data infra (spark, delta lake, airflow, looker); putting infra on actual rails; feedback loop in hours not days.

• Reduced deploy time 95%, dropped incident count, wrote rfcs, ran 1:1s, did perf reviews, technical leadership.

Health data platform.

• Implemented real-time flink on kinesis ingestion, 50x latency improvement.

• Orchestrated ml deploy + inference (docker, lambda, 200 req/s); cold starts be damned, the models shipped.

Cloud network infrastructure.

• Implemented rollout prioritization for config updates on backbone (b2) routers, keeping the internet stable even when engineering wanted to move fast with global changes.