Turning data platforms into durable business capability.

I build GenAI-powered analytics systems that turn complex data into self-serve insights and decisions.

Data, AI & Analytics Leader · Los Angeles, CA

About

I'm an enterprise data & AI leader who turns complex technology into trusted, real-time decisions — architecting lakehouse and agentic AI platforms that let Fortune-scale leaders act with confidence, not guesswork, at every level of the business.

Trusted decisions, not just dashboards

I build Databricks Genie-powered conversational analytics (Nalytics IQ) so leaders get plain-English answers they can act on immediately — replacing static reports with real-time, trustworthy intelligence.

Agentic AI that moves the business

I design and ship LangChain/LangGraph ReAct agents that automate multi-step business workflows end to end — from procurement decisions to data-quality checks — turning AI from a demo into measurable operating leverage.

Governance that earns executive trust

I extend enterprise-grade governance — security, lineage, auditability — into AI agent access and cost control, so leadership can scale AI adoption without scaling risk.

Technology in service of business outcomes

Every architecture decision I make is judged by the business impact it unlocks — faster decisions, lower cost to serve, and new revenue opportunities — not just technical elegance.

Work

01Product Studio

Nalytics IQ

Ask a question. Get the analysis.

An AI analytics agent on Databricks Genie that turns a plain-English business question into governed SQL, charts, and a written executive analysis — without an analyst in the loop.

One run, condensed to four moments: question, plan, comparison, exported report.

Questions it answers (sample)

List customers with a 20% or more decline purchase value in 2025 compared to 2024.
Identify clients completely inactive for the last 6 months.
What are the top 10 performing products in 2025, and how are they performing in 2026?
Provide a write-up on the journey of active brands.

Problem

Every new business question meant a ticket, a queue, and a bespoke report. Dashboards answered the questions someone anticipated last quarter, not the one a leader has right now.

Approach

A curated gold-layer semantic model the agent can reason over, governed end to end by Unity Catalog. A research agent plans the analysis as multiple steps, runs them, and writes up what it found.

Outcome

One question produces a four-step analysis plan, the SQL behind each step, comparison charts, narrative analysis, CSV download, and a multi-page PDF report — in seconds, not the days a reporting ticket used to take.

02Product Studio

Nexa

Try me

Any data. Any model. One conversation.

A personal product that connects to any cloud database, lets users bring their own LLM API key, loads selected schema, and turns plain-English questions into SQL, result tables, and auto-generated charts.

A product walkthrough: ask, plan, analyze, and explore business insights.

Features

Any data source: Databricks, Snowflake, MySQL, Google BigQuery, CSV, and other.
Flexible LLM integration: connect OpenAI, Anthropic, or Gemini with an API key, or use an existing Claude or GitHub Copilot login.
Schema browser: load tables, select tables, describe them in natural language.
Multi-line natural-language question box for richer business asks.
Results insight: surface the hidden truth behind the data, supported by a table and an auto-generated bar, line, or pie chart.
Read-only guardrail to prevent destructive SQL.
Zero- or low-cost self-service GenAI-based BI for business.

Positioning

Any Data → Intelligence Layer → Any LLM → Natural Language → Trusted Insights. Nexa is designed as a model-flexible intelligence layer between enterprise data platforms and the business users who need answers.

Approach

Users connect a data source, provide an OpenAI, Anthropic, or Gemini key, browse schemas, select safe tables, and ask a multi-line natural-language question. Nexa generates read-only SQL, runs it, and renders both the result set and an appropriate chart.

Outcome

The product demonstrates how governed natural-language analytics can work without locking users into one warehouse or one model provider — making trusted insights portable across data and AI stacks.

03Product Studio

SpeakIQ

Try me

Real-time AI call assistant.

A personal product that listens to a live conversation, shows a live transcript, and instantly suggests what to say next for interviews, sales calls, meetings, and support.

Problem

Live conversations move quickly, making it hard to retain every detail, respond clearly, and keep relevant context at hand — especially when the stakes are high.

Approach

SpeakIQ combines real-time transcription, system or tab audio capture, speaker separation, and configurable AI assistance to surface an in-the-moment, first-person response.

Outcome

A flexible conversation companion that gives users a live record of the discussion and context-aware help when they need to respond with clarity and confidence.

Features

Live transcript: real-time speech-to-text with interim results through the Web Speech API.
System or tab audio capture: transcribe the other party on a call, not just the microphone.
Speaker separation: label conversation turns as You and Them when both sources are captured.
Suggested responses: AI drafts a natural, first-person reply as the conversation develops.
Mode presets: Assessment, Sales, Meeting, Support, and General Q&A.
Your context: paste a resume, role, or product details to tailor suggestions.
Auto-suggest toggle: choose automatic suggestions or manual-only mode.
Flexible LLM integration: OpenAI, Anthropic, Gemini API keys, or an existing Claude or GitHub Copilot login.

Selected highlights

Retail Intelligence — AI-Powered Growth

Created an intelligent retail analytics experience that turns complex customer and business data into self-service insights. Empowered teams to discover growth opportunities, expand customer reach, and identify renewal risks earlier — driving 15% revenue growth, 10% customer-base growth, and 8% higher contract renewal rates.

AI AnalyticsGen AICustomer AnalyticsPredictive Insights

B2B ReAct Agent — LangChain & LangGraph

Designed a tool-use ReAct agentic AI system for B2B e-commerce that understands buyer/supplier queries, searches catalogs, compares vendor pricing, and reasons through multi-step workflows using LangGraph state machines.

LangChainLangGraphAgentic AIPython

Enterprise Databricks Lakehouse Platform

Designed and implemented a medallion architecture (bronze/silver/gold) on Databricks Lakehouse from the ground up, establishing modeling standards and Delta Lake best practices for a B2B marketplace serving 150K+ customers.

DatabricksDelta LakeAzureData Modeling

Unity Catalog Governance Framework

Implemented Unity Catalog namespace hierarchy for multi-domain data organization, enforcing row/column-level security and building comprehensive data lineage, dictionaries, and ERD documentation — the same governance discipline now extending to AI agent access and auditability.

Unity CatalogData GovernanceAI Governance

$20M+ Operational Impact via Data Optimization

Diagnosed and resolved Spark performance issues (data skew, small files, inefficient joins) and led SCD pattern implementation and pipeline modernization, contributing to $20M+ in measurable operational impact.

SparkPerformance TuningETL/ELT

Retail BI Automation — 1,400+ Locations

Automated analytics and reporting for 1,400+ retail locations at Sears Holdings, saving 120+ hours per week in manual reporting effort while partnering with business leaders on KPIs.

BI AutomationReportingRetail Analytics

Journey

Expertise

Generative & Agentic AI

Databricks Genie / Genie OneLangChainLangGraphReAct AgentsConversational AnalyticsAI Governance (Unity AI Gateway)

Data Modeling & Architecture

Dimensional (Kimball)Data Vault3NF (Inmon)NoSQLConceptual/Logical/Physical ModelingEnterprise Data Architecture

Lakehouse & Delta Lake

Databricks LakehouseMedallion ArchitectureDelta Live TablesUnity CatalogDelta LakeZ-Ordering

Multi-Platform Data

SnowflakeMongoDBAzure Data Lake StorageAzure Data FactoryCDCAPI Integration

Data Engineering & Optimization

Apache SparkETL / ELTSCD PatternsPerformance TuningData QualityPipeline Modernization

Governance & Standards

Row/Column-Level SecurityData LineageData DictionariesNaming ConventionsMetric Consistency

Tools & Technologies

SQLPythonDatabricksAzure (ADLS, ADF)ER/StudioMicroStrategyThoughtSpot

Data & Analytics Leadership

Data StrategyBI StrategyGlobal Team LeadershipExecutive CommunicationKPI DesignStakeholder Alignment

Experience

Jan 2022 — Present

Data, AI & Analytics · Forge (ex EmeraldX) — Los Angeles, CA

Lead enterprise data architecture, platform engineering, and BI strategy for a large-scale B2B marketplace, while driving the shift from static dashboards to agentic, generative AI analytics. Manage a global team of 8+ engineers and architects, building Databricks Genie-powered conversational analytics (Nalytics IQ), Unity Catalog governance, and medallion lakehouse design on Databricks and Azure from the ground up.

Apr 2018 — Dec 2021

Manager, Business Intelligence · Client: NBCUniversal | InfoCepts LLC — Los Angeles, CA

Led BI and Insights initiatives supporting digital media platforms and monetization strategies. Managed 20+ BI engineers and analysts across global teams, overseeing the end-to-end analytics lifecycle from ingestion to executive communication.

Jul 2017 — Apr 2018

Senior Software Engineer (Business Intelligence) · Client: Centene | Mastech Digital — St. Louis, MO

Optimized the enterprise BI ecosystem, reducing reporting artifacts by 30,000+ objects and improving platform performance while strengthening data governance and metric consistency.

Jun 2015 — Jul 2017

Architect / Senior BI Engineer · Sears Holdings — Chicago, IL

Designed and maintained large-scale BI dashboards for supply chain and merchandising performance. Automated analytics for 1,400+ retail locations, saving 120+ hours per week in manual reporting effort.

2007 — 2015

Earlier Roles · HCA, Citi Bank, Verizon Wireless, IL Dept. of Public Health, HPCL, Tata Motors

Progressively advanced through BI Engineering, Data Architecture, and Enterprise Analytics roles (Technical Specialist/Leader, Programmer Analyst, Assistant Data Manager, Project Manager), building strong foundations in SQL, statistical analysis, and large-scale reporting systems.

Education

MS, Management Information Systems

University of Illinois, USA · 2011

BS, Engineering

NIT Patna, India · 2007

Certifications

GitHub Copilot CertifiedAWS Solutions ArchitectAzure Data EngineerDatabricks Data EngineerAI/ML EngineerThoughtSpot Data ExpertMicroStrategy Architect

Let's connect

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Have a project in mind, or want to talk through data, AI, and analytics strategy? The fastest way to reach me is email.

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