I work with data and systems.
I build platforms, pipelines, and the unseen structures that keep them alive.
What interests me most is reliability, clarity, and reducing the accidental chaos in technology.

• Data Engineering: Python, SQL, Spark, Trino, Iceberg, ClickHouse, Kafka, Airflow, Postgres, Tableau / Superset
• Infrastructure & DevOps: Kubernetes (Amazon EKS), Terraform, ArgoCD, Jenkins, GitOps, Docker, Prometheus, Grafana, Alertmanager, AWS ecosystem, Cost Optimization
• Architecture & Governance: ETL / ELT Design, Data Modeling, Data Quality & Governance, RBAC
• AI & LLM Engineering: Vector Databases, Embeddings, RAG Pipelines

• 🧰 Data Forge – a modern data stack playground

  

I share notes on Medium — about data engineering, infrastructure, and AI.
Not as lessons to follow, but as experiments worth recording.

• Build systems that survive without their builders.
• Prefer the simple to the ornate, the reliable to the clever.
• Seek clarity in complexity, not to deny it but to shape it.

💡 “The task is not to chase novelty, but to strengthen what endures.”