Suranjan Rana Magar

Analyzed large-scale U.S. healthcare datasets to uncover trends, detect anomalies, and improve data accuracy; ingested and prepared millions of raw rows into central warehouses and maintained analytical infrastructure using Hive and Redshift to support reporting and exploration.

Designed and built scalable dbt data models and marts in Snowflake to enable self-service BI, reducing data preparation time by 90% and driving a 50% increase in new client subscriptions through performance and quality tracking.

Led end-to-end analytics workflows from ingestion to dashboards, applying Kimball methodology in dbt/Snowflake to enable 50+ project wins and implemented automated dbt tests and CI/CD to increase trust in reporting outputs.

Developed an IMDB-style movie website and a hardware inventory web app using React, TypeScript, and Laravel, improving user experience for asset tracking.

Delivered global workflow and email automation using Google Apps Script and optimized dashboards, creating one-click solutions that saved over 6 hours of manual effort per day and standardized a performance tracker used by 100+ projects.

Completed a Bachelor of Engineering in Computer Engineering (2015–2019) with coursework and practical focus on database design, data pipelines, and data warehousing including PostgreSQL and Snowflake.

Completed the Data Engineer in Python course on DataCamp focused on Python-based data engineering workflows and tooling.

Completed Databricks Lakehouse Fundamentals covering core Lakehouse platform concepts and fundamentals.