Christopher Khan

About

Backend/data engineer with production experience at Walmart and HealthSnap building Python services and data pipelines on AWS (EKS, Lambda, Glue, Airflow). Strong reliability and operations focus—implemented idempotency + circuit breakers for peak-traffic consistency issues, GitOps CI/CD, and observability. Demonstrated measurable performance wins (Postgres p95 45s to <5s, ~60% CPU reduction) and modernized SAS batch workflows to Python with parallel-run parity validation and feature-flagged rollout.

Key Strengths

• Designed and operated reliable Python microservices on EKS with OAuth/JWT auth, timeouts, retries, circuit breakers, and observability
• Resolved data consistency issues using idempotency keys, DB transactions, Kafka queuing, and reconciliation for eventual consistency
• Built GitOps CI/CD with Terraform/Helm and Argo CD enabling automated testing and progressive rollouts
• Scaling strategy based on SLOs and business signals (latency, concurrency, queue depth) with canaries, alarms, and rollback guardrails
• Delivered AWS Glue ETL from S3/PostgreSQL to S3 data lake/Redshift with schema evolution controls and data quality enforcement
• Improved SQL performance on large PostgreSQL datasets (p95 45s to <5s; ~60% CPU reduction) via indexing, partitioning, and batching
• Owned and remediated batch pipeline incident (Spark data skew/memory spills) with monitoring-driven triage and preventive refactors

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