Fractional Data Architect, Data Engineer, and Director-level analytics leader who steps in fast and delivers durable outcomes. 15+ years designing Snowflake and Azure data platforms, modern ELT/ETL pipelines, semantic models, and governed KPI frameworks across ERP, e-commerce, CRM, and SaaS ecosystems. Known for integrating messy systems, eliminating manual reporting, and creating executive-ready data foundations that teams trust and actually use. Over the past couple of years, I’ve focused heavily on AI enablement and intelligent automation. I design and deploy AI agents connected to governed data layers, implement n8n workflows for event-driven automation, and build internal tools that reduce repetitive work across finance, marketing, operations, and support teams. Available as a hands-on individual contributor or in fractional leadership roles (Director, Head of Data, CTO). My mix of operator-level execution and consulting experience makes it easy to step in, stabilize what exists, and improve it quickly.

Adam L.

Fractional Data Architect, Data Engineer, and Director-level analytics leader who steps in fast and delivers durable outcomes. 15+ years designing Snowflake and Azure data platforms, modern ELT/ETL pipelines, semantic models, and governed KPI frameworks across ERP, e-commerce, CRM, and SaaS ecosystems. Known for integrating messy systems, eliminating manual reporting, and creating executive-ready data foundations that teams trust and actually use. Over the past couple of years, I’ve focused heavily on AI enablement and intelligent automation. I design and deploy AI agents connected to governed data layers, implement n8n workflows for event-driven automation, and build internal tools that reduce repetitive work across finance, marketing, operations, and support teams. Available as a hands-on individual contributor or in fractional leadership roles (Director, Head of Data, CTO). My mix of operator-level execution and consulting experience makes it easy to step in, stabilize what exists, and improve it quickly.

Available to hire

Fractional Data Architect, Data Engineer, and Director-level analytics leader who steps in fast and delivers durable outcomes.

15+ years designing Snowflake and Azure data platforms, modern ELT/ETL pipelines, semantic models, and governed KPI frameworks across ERP, e-commerce, CRM, and SaaS ecosystems. Known for integrating messy systems, eliminating manual reporting, and creating executive-ready data foundations that teams trust and actually use.

Over the past couple of years, I’ve focused heavily on AI enablement and intelligent automation. I design and deploy AI agents connected to governed data layers, implement n8n workflows for event-driven automation, and build internal tools that reduce repetitive work across finance, marketing, operations, and support teams.

Available as a hands-on individual contributor or in fractional leadership roles (Director, Head of Data, CTO). My mix of operator-level execution and consulting experience makes it easy to step in, stabilize what exists, and improve it quickly.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
Intermediate

Language

English
Fluent

Work Experience

Director of Analytics at Ryman Hospitality Properties
February 1, 2023 - March 1, 2025
Led data initiatives across NetSuite, Shopify, AXS, MICROS POS, and warehouse data. Built a Snowflake warehouse and semantic models for sales and events, deployed forecasting pipelines improving event forecast accuracy by ~15%, and ingested POS/warehouse/event data in near real-time to power time-sensitive workflows and dashboards. Created secure internal APIs and a web UI to trigger Alteryx workflows, accelerating document processing. Established KPI definitions and RBAC to improve adoption across marketing, finance, retail, and operations.
Head of Analytics at Byte
January 1, 2019 - June 1, 2021
Migrated analytics stack from Azure/Microsoft to Snowflake/dbt/Fivetran, standardizing modeling and CI and delivering ~$300K annual savings (30%) with 50% faster queries. Partnered with data science to operationalize a core predictive model with feature enrichment and feedback loops. Built multi-touch attribution and near real-time CPA tracking across paid search, social, affiliate, influencer, and CRM, reducing CPA by 25% and increasing ROI by 40%; supported a ~$1B valuation.
Director of Analytics at American Addiction Centers
February 1, 2015 - September 1, 2018
Optimized multimillion-dollar media mix with a new reporting ecosystem, reducing patient acquisition cost by 30% and improving lead-to-admission conversion by 20%. Designed a predictive call routing system with skills-based routing, increasing enrollments by 18%. Scaled the analytics team from 1 to 5 and led governance and data literacy across marketing, sales, finance, and clinical analytics.
Regional Digital Marketing Strategist at Gannett | USA TODAY NETWORK
January 1, 2012 - January 1, 2015
Led regional digital marketing strategy and analytics initiatives, driving data-informed decisions to optimize campaigns and engagement.
Founder & Lead Consultant at ConversionGrow
December 31, 2006 - December 31, 2014
Consulted on digital marketing strategy, conversion optimization, and analytics for multiple clients, helping improve marketing performance and profitability.

Education

Bachelor of Science at Southern Polytechnic State University
February 11, 2026 - December 31, 2011
Now known as Kennesaw Statue University

Qualifications

Introduction to Gen AI with Snowflake
November 1, 2025 - November 30, 2025
Application Integration on Oracle Cloud - Oracle University
January 1, 2025 - February 11, 2025
The Data Scientist’s Toolbox - Johns Hopkins University
February 1, 2017 - March 31, 2017

Industry Experience

Healthcare, Software & Internet, Retail, Professional Services, Consumer Goods, Travel & Hospitality
    paper Snowflake Cortex AI Cost Calculator

    Snowflake Cortex AI Cost Calculator

    Purpose: Reference implementation for Cortex cost monitoring and forecasting

    A professional toolkit for tracking Snowflake Cortex service consumption and generating accurate cost projections. Perfect for engineering teams during scoping exercises and for clients managing their AI workload budgets.

    FEATURES

    • 16 monitoring views tracking all Cortex services
    • Query-level cost tracking - identify expensive queries
    • Document processing analysis - compare PARSE_DOCUMENT vs Document AI
    • Fine-tuning ROI tracking - separate training vs inference costs
    • Cortex Search optimization - hourly cost tracking to find idle periods
    • Latest pricing - Current rates for Cortex LLM models (15+ available)
    • Serverless task - automatic daily snapshots, no warehouse needed
    • Snapshot table - 4-5x faster queries
    • Simplified Cost per User Calculator for quick scoping
    • 30-day rolling totals for accurate estimates
    • Smart data fallback - works immediately after deployment
    • Historical trend analysis with week-over-week growth
    • Export-ready credit estimates for proposals
    • Zero disruption to production workloads

    Key Features

    Serverless Task (No Warehouse Required!)

    • Automatic daily snapshots at 3:00 AM
    • No configuration - Snowflake manages compute
    • Low cost: ~$0.30-1.50/month (vs dedicated warehouse)
    • Captures data to CORTEX_USAGE_SNAPSHOTS table

    Snapshot Table for Speed

    • 4-5x faster queries compared to ACCOUNT_USAGE
    • Pre-calculated metrics (no compute-on-query)
    • Historical tracking beyond 90-day rolling window
    • V_CORTEX_USAGE_HISTORY view includes week-over-week trends

    Simplified Cost per User Calculator

    • Moved to top of Cost Projections tab
    • Historical reference table shows actual usage
    • Simple persona configuration: name, user count, requests/day
    • Instant estimates for per-persona and total costs

    Smart Data Fetching

    • Automatic fallback: Tries snapshot table first, falls back to live view
    • Works immediately after deployment (doesn’t wait for 3 AM)
    • Best of both worlds: Fast when available, always functional

    Streamlined Experience

    • Removed Scenario Comparison tab
    • Clean documentation in docs/ folder (user-facing only)
    • Streamlined codebase for easy understanding
    • Essential files only for quick learning