Headline

Analytics Engineer | Python • SQL • Data Pipelines | AI-Powered Analytics & LLM Chatbots | Self-Serve BI & Automation | Product Analyst | Business Analyst

About

I build analytics systems that turn messy operational data into decision-ready intelligence. Over the last 6+ years, I’ve worked at the intersection of analytics engineering, automation, and applied AI, designing data pipelines, self-serve BI platforms, and internal analytics tools that allow teams to move from reactive reporting to real-time insights. My work typically involves building the full analytics stack: • Python + SQL data pipelines integrating CRM, ERP, and operational systems • Analytics warehouses and BI layers for self-serve reporting • Internal tools and automation that eliminate manual workflows • AI-assisted analytics systems that allow natural-language data querying A few examples of impact: • Built Python + Streamlit analytics apps that reduced multi-day manual AWS billing analysis to minutes • Designed BI systems used by leadership to monitor KPIs across sales, operations, and finance • Automated CRM → approval → SAP workflows eliminating manual operations work • Built ML models for forecasting and anomaly detection in business operations I enjoy working on ambiguous problems where business, data, and engineering intersect — building systems that replace Excel firefighting with scalable analytics infrastructure. Currently I’ve been building AI-powered analytics assistants that allow business users to query operational data using natural language. These systems combine LLM APIs, metadata repositories, and text-to-SQL workflows to generate accurate queries against analytics databases and return decision-ready insights. Core stack: Python • SQL • PostgreSQL • ETL Pipelines • BI (Power BI / Zoho / Metabase) • Machine Learning • APIs • Automation

Location

Bengaluru

AI stack

claude code

codex

gemini

hugging face

mcp

GroqCloud

Work experience

Business Analyst / Analytics Engineer at Frontier Business systems Pvt. ltd., Feb 2025 - Present · 1 yr 7 mos, Bengaluru, • Built a cloud-native GCP data pipeline extracting SAP B1 and CRM data across 50 tables using Apache Airflow and implemented timestamp watermark and MD5 hash-based change detection for incremental loads, landing raw data in GCS as Parquet before ingesting into BigQuery. • Modeled data in BigQuery using dbt — 56 staging models, 9 SCD Type 2 snapshots for historical dimension tracking, and mart tables partitioned by date and clustered by SBU, block, and KAM, reducing Power BI query scan cost. • Deployed GitHub Actions CI/CD pipeline with 3 workflows — automated DAG validation, dbt testing against isolated dev and QC BigQuery environments on every PR, and automated production deployment on merge to master. • Built a RAG-based metadata system storing column definitions, business rules, and query examples to improve text-to-SQL accuracy for the internal analytics chatbot. • Automated the end-to-end order-to-SAP workflow by integrating CRM data into a custom approval system, eliminating manual entry, cutting delays, and freeing operations staff for higher-value work. • Designed real-time Zoho Analytics dashboards connected directly to SAP, replacing static Excel MIS and enabling executives to monitor KPIs live. • Applied machine learning models (Decision Trees, Random Forest, XGBoost) to sales and operations data, delivering predictive insights that supported proactive decision-making. • Built internal AI-assisted development workflows using LLM copilots (ChatGPT, Claude, Gemini) to accelerate internal tool development and code optimization. • Built a Python + Streamlit analytics application to process AWS billing datasets, automating multi-day manual analysis and enabling self-serve cost analytics. • Collaborated closely with sales and finance leadership to ensure dashboards and predictive models addressed strategic business priorities

Business Analyst at Bharti AXA Life Insurance, Jul 2024 - Jan 2025 · 7 mos, Mumbai, Maharashtra, India, • Delivered CEO performance decks, consolidating data from multiple systems into executive-ready insights that influenced board-level discussions. • Built interactive dashboards in Power BI and SQL, giving real-time visibility into policy performance, customer behavior, and claims operations. • Automated recurring MIS reports with Python scripts, reducing turnaround time by 40% and improving reliability of reporting. • Developed predictive analytics POCs (classification & regression models) to forecast sales and customer churn, showcasing the potential of machine learning in insurance decision-making. • Ensured data quality and governance by implementing validation checks and cleansing routines, enhancing trust in analytics outputs. • Partnered with leadership and cross-functional teams (sales, operations, finance) to translate business needs into data-driven recommendations

Data Analyst at Kenko Health, Jul 2022 - Jun 2024 · 2 yrs, Bengaluru, Karnataka, India, • Automated high-volume insurance operations with Python (Postgres + Excel), cutting endorsement processing from days to same-day and delivering faster customer onboarding & policy servicing. • Built real-time CRM and Sales dashboards on Hubspot, Metabase, and Apache Superset, enabling leadership to spot drop-off stages and drive higher conversions. • Designed reconciliation workflows across insurance MIS, Hubspot CRM, and Digit Insurance partner logs, ensuring accurate claims tracking and enabling successful financial recovery. • Automated member ID mapping by integrating Kenko’s system files with Digit-issued IDs via Python, eliminating manual effort and improving data accuracy in policy management. • Supervised and developed a 3-member analyst team, guiding them on automation and dashboard.

Management Information System Executive at HEALTH PRIME SERVICES (INDIA) PRIVATE LIMITED, Dec 2015 - Aug 2017 · 1 yr 9 mos, Mumbai, Maharashtra, India, • Prepared client-specific MIS reports, ensuring accurate tracking of operational and financial performance. • Developed VBA macros to automate recurring reporting tasks, reducing preparation time from 4 days to 3 days. • Improved data consistency and report reliability by standardizing reporting processes across teams. • Coordinated with cross functional teams to gather data from various sources.

Education

Bachelor of Management Studies, Prahladrai Dalmia Lions College of Commerce and Economics Sundar Nagar S V Road Malad West Mumbai 400 064