Available for Select Analytics & AI Builds
Turning messy data into
decisions you can trust.
Messy Data
Scattered sources.
Inconsistent. Hard to use.
Clean & Structure
Remove noise. Standardize.
Bring clarity.
Analyze & Extract
Find patterns. Deep insights.
Answer the right questions.
Trusted Decisions
Reliable insights. Confident
decisions. Real impact.
I'm Abhishek — a Senior Data Analyst with 6.5+ years driving measurable growth across ad-tech, ed-tech, and digital commerce. I've helped teams grow revenue by 22%, automate reporting across 50+ enterprise brands, eliminate 20% of data discrepancies, and build the single-source-of-truth systems that make numbers trustworthy in the first place.
+22%
Revenue Growth
Variance & Quota Modeling
50+
Brands Automated
SQL / BigQuery Views
-20%
Discrepancies
SSOT & Anomaly Detection
+25%
Completion Lift
LMS Funnel Telemetry
EXPERIENCE DELIVERING DATA SYSTEMS & REVENUE ANALYTICS FOR TEAMS AT
Reddit (via iOPEX)
Novatr
magicpin
iOPEX Technologies
Anthropic AI Certified
Core Disciplines
What I Do
I work at the intersection of revenue analytics, data quality, and applied AI.
REVENUE & INSIGHTS
Analytics & Forecasting
Pipeline forecasting, KPI governance, and stakeholder dashboarding engineered to spot trends and risks before they affect targets.
DATA INTEGRITY
Data Quality & SSOT Systems
Building single-source-of-truth frameworks, anomaly detection, and validation checks that teams actually trust.
PRACTICAL AI
Applied AI Tooling
Practical, lightweight AI agents and utilities, including private tools that run entirely in your browser without sending data anywhere.
SYSTEM ARCHITECTURE
The Modern AI-Ready Analytics Stack
How I engineer clean data foundations that turn fragmented databases into trustworthy metrics and proactive agentic workflows.
BUSINESS IMPACT & ROI
The Transformation: Before vs. After
What happens when you replace spreadsheet firefighting and silent warehouse discrepancies with automated, production-grade analytics.
TRADITIONAL CHAOS
Conflicting Numbers & Disputed Dashboards
Three different teams bring three different revenue numbers to Monday leadership meetings. Executive time is wasted debating whose spreadsheet is right.
ENGINEERED SSOT
Unified Semantic Layer & Single Source of Truth
Automated dbt metric models serving one canonical definition. Product, Finance, and Exec dashboards pull from the exact same audited data contracts.
REACTIVE FIREFIGHTING
Silent Failures Discovered by Angry Stakeholders
Upstream API schema shifts or missing values corrupt downstream metrics unnoticed for days or weeks until a VP spots a broken graph.
PROACTIVE TELEMETRY
Automated Anomaly Tests & Slack Alerts in 2 Mins
Automated row-count, null-percentage, and distribution checks trigger instantaneous Slack alerts with root-cause diagnostic queries before reports publish.
MANUAL DRAG
60% of Senior Analyst Time Trapped in Ad-Hoc SQL
High-paid analytics engineers drown in repetitive 'Can you pull this CSV?' requests, creating multi-day bottlenecks for product and marketing.
10X LEVERAGE
Self-Serve Semantic Models & Agentic AI Tooling
Self-serve exploration layers and in-browser AI assistants allow business users to safely answer 80% of routine questions autonomously.
SILENT CLOUD BURN
Unbounded Full-Table Scans Wasting Cloud Budget
Unpartitioned legacy queries scan terabytes of historical events repeatedly, burning through thousands in Snowflake credits and BigQuery query quotas.
COST OPTIMIZED
Optimized Partition Pruning & 70–85% Less Scan
Partition clustering, incremental materialization, and query refactoring eliminate redundant warehouse scans and drastically slash monthly compute bills.
10–15 hrs
Saved per analyst / week on manual ad-hoc requests
70–85%
Reduction in warehouse compute & full-table scan waste
< 2 mins
Anomaly isolation and automated team notification
FEATURED CASE STUDY
Revenue Data Reconciliation & Anomaly Agent
A production monitoring system that catches data quality issues before they reach an executive dashboard — combining rule-based detection with AI-generated narrative summaries.
Read the case study
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Ready to Solve a Data Problem?
Book 30 minutes to untangle a specific SQL, pipeline, or architecture bottleneck — or send an email to discuss a larger project.