Kevin Chen

I’m a Senior Data Engineer with 10 years of experience building scalable data platforms and distributed processing systems across streaming media, healthcare, and SaaS environments. I focus on real-time analytics, recommendation systems, AI/ML data infrastructure, and platform reliability that helps teams make business-critical decisions.

At Spotify, I developed a Streaming Personalization & Recommendation Analytics Platform that supports large-scale experimentation and machine learning workloads. I rebuilt ingestion and orchestration workflows with Airflow and incremental processing to reduce end-to-end data latency from hours to under 15 minutes, and I automated infrastructure provisioning and deployment with Terraform, Kubernetes, and GitHub Actions—cutting deployment lead time by 60%.

I also drive measurable improvements in trust and stability: I introduced data quality checks and lineage validation across critical pipelines, lowering production data incidents by 30%+ and improving downstream reporting stability. I optimized Snowflake workloads through clustering, partitioning, and tuning to reduce annual compute spend by ~20%, and I strengthened operational reliability for business-critical pipelines to reduce SLA breaches by 35%.

Previously at Included Health, I built a HIPAA-compliant Unified Healthcare Data & Patient Analytics Platform by developing Airflow and Spark pipelines ingesting patient eligibility, claims, and clinical records from Kafka streams and systems like Salesforce and microservices. I consolidated fragmented pipelines into a centralized AWS data platform, created reusable ingestion/transformation frameworks that reduced onboarding time and increased self-service adoption by 30%, and maintained 99%+ DAG success rates through automated validation, retry handling, and monitoring.