I turn messy, disconnected data into dashboards and reports that people actually use to make decisions. Right now I'm a Data Analyst at E Machines Technologies, where I build Power BI dashboards tracking machine sales, service TAT, and spare parts utilization — and I use Databricks + PySpark + SQL to automate reporting workflows that used to eat hours of manual work (cut refresh time by 30%). Before that, I worked as a Data Analyst Intern at Labmentix, building end-to-end pipelines using Delta Live Tables and the Medallion Architecture (Bronze → Silver → Gold). What I bring: — SQL & Python (Pandas, NumPy, PySpark) for cleaning and transforming data at scale — Power BI & Tableau for dashboards stakeholders can self-serve from — Databricks, Delta Lake, and ETL/ELT pipeline design for data that's actually trustworthy — A habit of asking "who's going to use this, and what decision will it change?" before I build anything I've applied this across e-commerce (50K+ transaction segmentation), HR analytics (attrition drivers across 5K+ employee records), and regional sales performance (25K+ rows across 5 regions) — always with the same goal: make the data boring to argue with. Open to Data Analyst / BI / early Data Engineering roles where I can own reporting end-to-end. 📩 Prakhartyagi.rke@gmail.com
