Senior Data Analyst | BI & Product Analytics | Ex- Ola Electric - River


Bengaluru, Karnataka, India







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Senior Analyst with 4+ years partnering with product, engineering, and business teams at fast-moving, product-driven organizations. Built and scaled a real-time data-logging platform on Google AppSheet to 50+ engineers, cutting manual data entry by 99% and saving 15+ hours weekly. Skilled in SQL, Python, Power BI, Looker and Tableau turning fragmented, high-volume data into KPI-driven dashboards leadership acts on
Bengaluru
anthropic apis
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codex
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Business Analytics Consultant at Self-Employed, May 2025 - Present · 1 yr 4 mos, • Designed and implemented a Google AppSheet platform to digitize inventory and sales tracking processes. • Delivered Looker Studio dashboards, enhancing real-time visibility into operations. • Streamlined manual tracking through a centralized digital workflow, significantly improving accuracy and reporting.
Senior Data Analyst at River, Jul 2024 - Mar 2025 · 9 mos, Bengaluru, Karnataka, India, • Launched a Google AppSheet app for real-time ride logging, adopted by over 30 engineers, reducing manual entry by 99%. • Analyzed large datasets using SQL and Python to uncover trends and support data-driven decision-making. • Engineered SQL & Python ETL pipelines for CAN data, accelerating analysis turnaround by 60%. • Collaborated with engineering and product teams to define and manage key performance indicators (KPIs).
Senior Associate Data Analyst at Ola Electric, May 2023 - Jul 2024 · 1 yr 3 mos, • Analyzed EV telemetry and operational data using SQL, Python, and Azure Data Explorer (KQL) to enhance vehicle performance. • Developed automated Power BI dashboards to track over 25 KPIs for more than 50 stakeholders. • Conducted root-cause analysis to uncover warranty failure patterns, driving data-backed decisions. • Collaborated with engineering, testing, and business teams to investigate data trends and identify issues.
Associate Data Analyst at Ola Electric, Jan 2022 - May 2023 · 1 yr 5 mos, • Reduced reporting turnaround time by 80% through SQL-based pipeline automation. • Streamlined weekly processing time from 8 hours to just 45 minutes using Python and App Script for CSV automation. • Standardized over 12 recurring reporting workflows across multiple teams, fostering collaboration and consistency.