Sriram Narayanan

I am a Data Engineer with several years of experience designing, building, and maintaining production-grade data pipelines and platforms in regulated and high-impact environments. My work has involved end-to-end ownership of data systems, including ingestion from multiple sources, schema management, validation, orchestration, monitoring, and incident handling.

I have strong hands-on experience with Python, SQL, PySpark, and AWS, and have worked extensively with orchestration frameworks such as Airflow, Dagster, and Kedro. I place a high emphasis on data quality, observability, and reliability, and I enjoy digging deep into datasets to understand anomalies, improve performance, and make systems more robust and scalable.

I work closely with product, analytics, and data science teams to translate business requirements into reliable technical solutions, and I enjoy environments where I can take ownership, continuously improve systems, and learn new domains quickly.

Beyond my professional work, I’m deeply interested in robotics, computer vision, and underwater vehicles. I enjoy exploring how software, data, and AI intersect with real-world systems, and I’m particularly excited by roles that combine strong engineering fundamentals with applied AI and large-scale data problems.