I’m a data engineering practitioner focused on building reliable, business-driven data systems.
I work primarily with Python, SQL, Apache Airflow, and AWS, designing and implementing ETL pipelines that transform raw data into decision-ready assets. My focus is not just on moving data — it’s on building pipelines that are maintainable, automated, and aligned with measurable business impact.
I apply Lean thinking to data engineering by eliminating unnecessary data movement, reducing operational friction, and prioritizing simplicity in system design. I optimize for clarity, automation, and long-term maintainability rather than quick fixes.
I’m particularly interested in designing scalable data workflows that support decision-making at scale. My goal is to grow into a data engineer who not only writes clean code but architects efficient, production-grade data platforms.
