Bengaluru, Karnataka, India
Data Analyst with hands‑on experience building automated ETL pipelines, cloud‑based data workflows, API integrations, and real‑time analytics systems. Strong expertise in Python, SQL, PostgreSQL, Neon DB, Metabase, and workflow automation using GitHub, Fast Cron and Google Apps Script. Proven ability to design scalable data architectures, automate reporting processes, and deliver high‑impact business insights. Adept at transforming manual processes into fully automated pipelines, improving reliability, efficiency, and decision‑making across operations and finance teams.
• Designed and deployed a fully automated ETL pipeline using Python, GitHub Actions, FastCron, NeonDB, and Metabase, replacing manual Jupyter workflows and enabling real‑time sales tracking that contributed to a 30% increase in sales. • Automated operational reporting using Google Apps Script, generating HTML‑styled reports and reducing manual effort by 70%. • Designed and maintained Power BI dashboards for operations and finance, improving decision efficiency across 200+ stores. • Fully automated delivery of Food Cost, Sales, Franchise, IGCC, Serviceability, and other operational reports through Python + Apps Script workflows, eliminating manual reporting effort. • Improved data quality by implementing missing‑value imputation, outlier detection, and consistency checks across multiple data sources. • Conducted behavioral pattern analysis to detect fraud in IGCC and ORS systems, reducing fraudulent refunds by 40%. • Built advanced Excel analytics for forecasting and food‑cost variance analysis. • Delivered ad‑hoc analytical reports to cross‑functional teams, supporting business operations and leadership decisions. • Leveraged ChatGPT and Copilot to accelerate Python ETL development, automate report generation logic, and reduce manual coding time by 40%.
• Performed cleaning process in Excel of user recipes and ingredient data, exported them to database. • Applied data mining techniques on user interactions, food recipe trends, and cooking preferences to identify insights like most popular recipes, user cooking habits, and common ingredient. • Built Power BI dashboards tracking user engagement, conversions, and upload trends .