Hey, I'm
Marketing Analyst — Data & Automation
Data Analytics · Automation · Cloud Pipelines · Performance Marketing
I turn marketing data into decisions — building automated pipelines and dashboards on GCP (BigQuery, Colab Enterprise, Looker Studio) and MySQL.
Marketing Analyst at Maino AI, focused on data analytics and automation. I build automated data pipelines, dashboards, and reporting on Google Cloud Platform — BigQuery, Colab Enterprise, Looker Studio, and MySQL — for performance-marketing clients including Amazon MX Player, Hyugalife, Nutrabay, MillD, and Hi-Robin.
Previously at Aristok Technologies, I managed Meta & Google Ads for brands like Porter — reducing customer acquisition cost through data intelligence, building Python/Streamlit dashboards, and automating performance workflows end-to-end. My approach pairs hard analytics with a marketer's sense for what moves the number.
Turning data into revenue through performance marketing and automated systems.
End-to-end media buying and bid optimization across Meta and Google Ads. Specializing in CAC reduction, budget pacing, and full-funnel strategy.
Building automated, real-time reporting systems using BigQuery, Python, and Looker Studio. I turn scattered data into actionable stakeholder dashboards.
Engineering agentic AI skills for in-product AI agents and automating reporting workflows — from Root Cause Analysis to creative analysis of video & static ads.
Data & automation for performance marketing — across a marketing-AI platform and a growth agency.
Apr 2026 – Present
Jun 2025 – Mar 2026
Jun 2024 – May 2025
From engineering student to performance marketing analyst — a path driven by data.
Electronics & Telecommunication at Vishwakarma Institute of Technology, Pune
FoundationLed The Investment Forum & E-Cell — organized events, managed teams, built networks
LeadershipWireless Controlled Drainage Cleaning Robot — IoT & Robotics innovation
InnovationStarted as Business Analyst intern — managed Meta & Google Ads for Porter
Career StartSpotlight of the Month & Best Turnaround Story — reduced CAC from ₹750 to ₹400
RecognitionPromoted to full-time — built BigQuery pipelines, AI agents, and custom dashboards
GrowthAutomatic Number Plate Detection & Recognition — Computer Vision research
ResearchJoined Maino AI — data analytics & automation on GCP (BigQuery, Colab Enterprise, Looker Studio, MySQL) for performance-marketing clients
Current ChapterProjects and solutions I've built — from data pipelines to AI agents.
Chat with your data across BigQuery, Google Ads & Meta Ads
Marketing analysts spent hours writing SQL, switching between ad platforms, and manually assembling reports. Non-technical stakeholders couldn't access data without going through analysts — creating bottlenecks across siloed data sources.
Built an AI-powered conversational agent that autonomously discovers schemas, writes & executes SQL, pulls live data from ad platforms, and generates interactive visualizations — all through natural language chat.
From ad platforms & databases to live dashboards — fully automated
Marketing data lived in scattered sources — ad platforms, spreadsheets, and databases — outgrowing spreadsheet limits and burning hours on manual CSV exports and reconciliation.
Architected a cloud pipeline on Google Cloud Platform — BigQuery as the warehouse, Colab Enterprise and MySQL for processing, surfaced in Looker Studio — automated end-to-end on a daily schedule.
Stack: GCP · BigQuery · Colab Enterprise · MySQL · Looker Studio · Python · Apps Script · Clients: Amazon MX Player, Hyugalife, Nutrabay, MillD, Hi-Robin
Read the Full BlogLive simulated reporting for an Indian retail client
An interactive, automated dashboard pulling simulated data from Meta and Google Ads, calculating blended ROAS, Spend, and Revenue in real-time. Try hovering over the charts below (Built with Plotly.js).
Live updates directly from my LinkedIn profile.
Practical write-ups on ad platforms, testing, SQL and using AI on real business data.
AI agents can now pause ads and move budgets. Why a wrong action costs far more than a wrong answer, and the permission setup that keeps an agent useful without letting it run up a bill.
AI analyticsEight real limits of AI data analysts — why each one exists, which are shrinking, and four tests to run before you trust one with a board-deck number.
AI analyticsAn AI-written query can run cleanly and still answer a different question. Seven quick checks — from the table it chose to timezones and refunds — that catch silent failures before a number reaches leadership.
AI analyticsA metric definition in a prompt is a suggestion the model usually follows. In a semantic layer it is fixed SQL. Where each belongs, a simple test for deciding, and a one-week way to start.
AI analyticsLLMs invent column names because they can't see your schema. Four engineering layers — retrieval, constraint, dry-run validation and repair — fix it without a bigger model, plus the one failure they can't catch.
Ad testingTwo identical ads can show a 20% gap by pure chance. How much data a creative test really needs, why peeking manufactures winners, and a protocol for calling results honestly.
Validated expertise in marketing, AI, and e-commerce through industry-leading programs.
Click any skill to learn more about my expertise.
Vishwakarma Institute of Technology, Pune
I'm always open to discussing new opportunities, marketing challenges, or just having a chat about data and automation.