Manager, Analytics Engineering
I lead data & analytics engineering — owning the modern data stack end-to-end, building the teams and pipelines behind it, and bringing AI into the analytics workflow. 10+ years turning messy source data into decisions executives trust.
About
I'm a Manager of Analytics Engineering with 10+ years across Business Intelligence, Data Engineering, and analytical modeling. Today I own the analytics platform and modern data stack end-to-end — and lead the engineers who build on it.
I've built across e-commerce, retail, D2C, B2B, and luxury & lifestyle brands — unifying DTC, wholesale, retail-store, and marketplace data into one trusted source of truth for the business.
My work spans the full lifecycle: data & analytics engineering (ingestion, warehousing, orchestration, modeling), self-service BI, and increasingly AI woven into the everyday workflow. I've led org-wide platform migrations, set engineering and SQL standards, mentored teams, and partnered with senior stakeholders across Editorial, Marketing, Merchandising, Retail, and Finance.
Expertise
Own the modern data stack end-to-end — Fivetran ingestion, Redshift warehousing, Airflow orchestration, and version-controlled, modeled fact/dimension tables. I replace manual steps with scheduled, observable, reliable pipelines.
Manage and mentor analytics engineers, set technical direction, and establish code-review, SQL-style, and governance standards. I've led org-wide platform migrations and driven a culture of data democracy across the business.
Weave LLMs, agentic workflows, and automation into the analytics stack — internal AI assistants over company data and AI-assisted pipeline, reporting, and QA work that shorten the path from question to answer.
AI in practice
AI isn't a side project — it's part of how my team ships analytics every day. I build with LLMs, agentic workflows, and the Model Context Protocol (MCP) to connect our data, tools, and people, and to take the repetitive work off engineers' plates.
Internal AI assistants that let non-technical teams ask questions of company data in plain language and get governed, trustworthy answers — without writing SQL or waiting on a request queue.
Agent-driven workflows (n8n + MCP) that assemble multi-source reports, run recurring ETL, and deliver briefs straight to the channels stakeholders already use — turning manual reporting into a hands-off pipeline.
Using LLMs day-to-day to accelerate pipeline development, SQL and data modeling, documentation, and data-quality checks — raising throughput and consistency across the team.
Wiring AI into the stack through MCP integrations across our data warehouse, BI, marketing, and e-commerce tools — so insight, automation, and action live in one connected workflow.
Toolbox
Portfolio
Led the organization-wide migration of the BI platform, re-architecting the self-service layer and scaling adoption to 40+ active users and 3,000+ self-service queries — advancing a culture of data democracy with no disruption to executive reporting.
Architected and led the analytics migration from Spree to Shopify — re-engineering downstream data models and pipelines end-to-end with zero disruption to executive reporting through the cutover.
Built and maintained Airflow DAG pipelines ingesting from external APIs — Meta, TikTok, and Amazon — unifying marketing, advertising, and marketplace data into modeled, query-ready Redshift tables for the analytics layer.
Bringing AI into the analytics workflow — internal LLM-powered assistants over company data and agentic automation for recurring reporting and ETL — so non-technical teams get answers faster and engineers spend less time on toil.
Keep the analytics platform running seamlessly end-to-end — maintaining all data pipelines and automated flows, monitoring and resolving data-quality issues before they reach stakeholders. As BI platform admin I own access, governance, and reliability, and I run project planning and delivery from intake through ship.
An interactive, CEO-facing financial model mapping a path to a 10× revenue target by tuning the core e-commerce levers — traffic, conversion, AOV, and purchase frequency — with live scenario toggles.
Career
Education
M.S., Information Technology & Management
Campbellsville University — Louisville, KY
M.S., Electrical Engineering
Fairleigh Dickinson University — Teaneck, NJ
B.Tech, Electronics & Communications Engineering
Jawaharlal Nehru Technological University — India
Hiring for data, analytics, or platform leadership — or want to talk about bringing AI into your analytics stack? I'd love to hear from you.