AI and software
Product reporting, creator programs, competitive analysis, and AI-assisted insight.
OpenAI, Meta AI, Elastic, ManychatSenior analytics engineer · Data platforms · Toronto
I build data systems humans and AI can trust.
I turn messy source data into reliable models, reporting, and AI tools. I also work with the humans who use them, because good engineering only matters when it helps someone make a better call.
Clients I've Worked With
10Selected work
Ten principles. Ten projects.
Ten systems that changed how real teams reported, governed data, and used AI.
01 · Speed
33.3× Faster Dashboards
How one Sigma dashboard went from ten widget-level query paths to a shared data model — and how to make the same kind of change without changing what the numbers mean.
2026Read the study
02 · AI Readiness
Trusted AI Answers For Leadership
How a governed data layer taught Cortex the grain, joins, and metrics — and stopped a fluent guessing machine from reaching the humans who needed it.
2026Read the study
03 · Reliability
16M Rows, Precisely Orchestrated
How one scheduled root and a Snowflake task graph replaced guessed wait times — and kept incomplete refreshes from reaching dashboards.
2026Read the study
04 · Correctness
700k-Scale Identity Resolution
How graph-based identity resolution replaced a manual linking queue that could not keep up with tens of thousands of new creators each month.
2026Read the study
05 · Security
One Secure Data Policy
How a four-switch Sigma policy replaced hard-coded workbook access across hundreds of clients with composable organization, agency, division, and brand permissions.
2026Read the study
06 · Prevention
99% Fewer Data Errors
How a checker inside a shared spreadsheet stopped bad campaign links at the moment of entry — and broke an endless correction loop before reporting.
2025Read the study
07 · Documentation
Answers for 30+ Teammates
How a versioned GitHub atlas replaced word-of-mouth warehouse knowledge — so 30+ teammates and their agents could stop chasing the person who knew.
2026Read the study
08 · Insight
Criticism Into Creative Direction
How sentiment, LLM topic analysis, and human review turned scattered criticism into a simple “do this, not that” brief, then checked the lesson against a later campaign with 86.8% positive sentiment.
2025 to 2026Read the study
09 · Efficiency
75% Less Storage. 84.6% Less Peak Memory.
How content hashes cut storage for repeated job text by 75% while a bounded publisher cut peak VPS memory from about 7 GB to 1.078 GB, without losing job history.
2026Read the study
10 · Agent Tooling
146 Agent Tools. One Balanced Ledger.
How AI handles changing statement formats, match rules classify the known cases, and a double-entry ledger turns scattered financial data into a personal CFO.
2026Read the study
What humans say
Trusted with hard work. Easy to work with.
Exact words from humans who worked beside me and reviewed my work. Names are hidden for privacy.
“Paul was one of the most dedicated and reliable teammates I've ever worked with. He has a gift for explaining complex topics in a clear and didactic way, making collaboration seamless and productive.”
Former teammate · Touché! · LinkedIn recommendation, 2025
“Working with Paul was like watching a masterclass in marketing science automation. He doesn’t just believe in clean, precise data—he builds the systems that make it happen, over and over again.”
Former teammate · Touché! · LinkedIn recommendation, 2025
“His work has not only improved data accuracy by nearly 99 percent but has also shifted the internal culture toward one of high trust and data-backed confidence.”
Manager · Viral Nation · Year-end review, 2025
“Paul’s ability to solve ambiguous technical challenges while maintaining a selfless, team-first mindset makes him an invaluable asset to the organization.”
Manager · Viral Nation · Year-end review, 2025
Experience
The work got broader. The standard stayed high.
I moved from hands-on automation to reusable measurement, then to data platforms and AI. The titles and dates come from my work record. The details come from code, project files, and performance reviews.
Mar 2025 to present
Analytics Engineer, Business Intelligence
I work as an analytics engineer and solution architect for reporting and AI.
I build the shared Snowflake data layer behind dashboards and AI products. A 16-million-row model made median Sigma queries 33.3× faster, from 9.6 seconds to 0.29 seconds, with zero system errors across 4,116 launch queries. I also built data orchestration across four creator programs that cut month-long approval work to 2–3 days, a governed AI layer with 24 reusable metrics and 32 verified questions, and identity matching that reduced fragmented creator records by 36.6%.
Aug 2023 to Mar 2025
Supervisor, Marketing Science
I was a measurement leader for major national client accounts.
I led measurement for Canadian Tire, WestJet, HSBC, and Canada Post, connecting KPIs, data, and recommendations to media decisions. I built a Domo, Python, and SQL pipeline that automated competitive intelligence reporting, cut production from 1–2 months to one week, and generated more than $200K in new billings. I also managed three analysts, coached the team in SQL, Python, dashboards, and privacy-safe data clean rooms, and won Creative of the Year for marketing science automation.
Oct 2021 to Aug 2023
Senior Analyst, Marketing Science
I was a hands-on analytics builder who turned repeat measurement work into reusable systems.
I built Observer, a Domo data-governance system that automated lineage, ownership, and quality alerts. It cut anomaly detection from days to minutes and saved 20 hours of manual monitoring each week. I also built reusable SQL, Python, and R analysis patterns for customer journeys, conversion, loyalty, audience overlap, and category movement, giving the team a tested starting point for repeat client questions.
Mar 2019 to Nov 2019
Data Analyst, Data Science
I was a data analyst focused on making campaign and billing data trustworthy.
I combined campaign and finance data, checked invoices, and followed up with media partners when something did not match. After spotting a slow manual process, I learned VBA and built an invoice-matching tool in two weeks that saved the billing team more than 20 hours each month.
Breadth
Different industries. The same standard.
Clear definitions, reliable data, useful analysis, and results humans could explain.
Social platforms
Campaign measurement, content analysis, reporting systems, and data quality.
Meta, Facebook, InstagramConsumer technology
Launch reporting, audience analysis, social listening, and QBR measurement.
Meta Quest, Ray-Ban Meta, RoborockHousehold and personal care
Multi-brand reporting, benchmarks, paid media analysis, and quality checks.
Kimberly-Clark, Kleenex, Huggies, Cottonelle, Pull-Ups, Goodnites, Poise, DependRetail and ecommerce
Customer journeys, conversion, loyalty, campaign reporting, and sales analysis.
Canadian Tire, Vans, Polywood, OakleyAutomotive
Dealer performance, target automation, campaign measurement, and reporting design.
Audi, Volkswagen, Stellantis, Chrysler, Dodge, RamFinancial services
Privacy-safe media exposure, reach, frequency, sequence, and conversion analysis.
HSBCTravel and logistics
Digital behavior analysis, reporting, and measurement infrastructure.
WestJet, Canada PostFood and beverage
Portfolio measurement, campaign analytics, and consumer behavior research.
Diageo, Campbell'sEducation
Digital analytics implementation and measurement planning.
McMaster UniversityTechnology
Technology behind the work.
Twenty-one tools used across data warehouses, BI, engineering, analysis, and AI.
SQLSQL
Snowflake
Google BigQuery
Looker
DOMODomo
Python
pandas
Git
R
scikit-learn
Google Apps Script
Streamlit
Claude Code
ChatGPT Codex
Google Gemini
JavaScript
TypeScript
Node.js
React
HTML5
CSS
What we can build
Let’s build the system that moves your whole team forward.
I bring reporting, metrics, and AI together on one trusted foundation, so humans can move faster and take on more ambitious work.