mnelson.ca

I build AI-native data platforms — and multiply the teams that run them.

Matt Nelson · P.Eng · Berkeley MIDS · 10 years in data, 16 in engineering · Calgary, Canada

The path so far

  1. 2005–2010

    University of WaterlooBASc Chemical Engineering

  2. 2006–2010

    Engineering Co-opLanmark · Olds Gas Plant · Pengrowth

  3. 2010–2014

    Pengrowth EnergyProduction & Exploitation Engineer

  4. 2014–2017

    Centrica EnergyExploitation / Development Engineer

  5. 2016–2018

    Berkeley MIDSMaster of Information & Data Science

    Master of Information and Data Science at UC Berkeley (3.89 GPA) — completed nights-and-weekends while working full-time. The pivot point where a decade of engineering turned into a data career.

  6. 2017–2022

    Canlin EnergyCorporate Data Scientist & Reserves Manager

    Drove the transition to self-service data: implemented Tableau company-wide (100+ data sources, 50 workbooks in year one) and owned the regulated annual reserves evaluation feeding audited financial statements.

  7. 2022–2024

    Canlin EnergyData & Advanced Analytics Lead

    Designed, built, and ran Canlin’s modern data stack (dbt Cloud, Snowflake, DataRobot) and led IROC (remote operations centre) analytics — mentoring junior professionals into data roles along the way.

  8. 2024–2025

    Paramount ResourcesSenior Data Analytics Engineer

    Senior IC on the Data Analytics and Integration team — corporate PowerBI dashboard suites, Streamlit optimization apps, and governance-level advocacy for a modern cloud data stack.

  9. 2025–2026

    StackDXData Platform Engineer

    Lead engineer on the US data platform rebuild: a legacy Python ETL stack replaced with a production Dagster architecture — 15 states, 945 transformation assets, a 3.8 TB source layer distilled to a 10.3 GB exposure layer serving 300M+ records — shipped AI-first with a custom Claude Code toolchain. Read more

  10. 2026–now

    StackDXProduct Manager, Stack Maps & Public Data

    Product Manager for Stack Maps and the Public Data team — a 6-person group across two countries — setting roadmap while still shipping in the codebases the roadmap depends on.

Flagship projects

  1. 2014

    P.Eng designationAPEGA, 2014

    Professional Engineer designation (APEGA) — the licensed-engineering rigor that underwrites every production system since.

  2. 2017–2022

    Reserves evaluation ownership+$730M technical revisions

    Owned the externally-audited NI 51-101 reserves evaluation for five years — the board-level valuation of every corporate asset. Rigorous data and engineering work added +$730M (NPV10) in technical revisions. Read more

  3. 2021–now

    twochannel.ai18k+ products · one engineer

    Founder project: an AI-assisted HiFi catalog and system designer where LLM-in-the-loop pipelines maintain 18k+ products across 2k+ brands. The catalog is the size that would normally need a small data team behind it, and there is only me. Read more

  4. 2022–2024

    dbt + Snowflake platformCanlin’s data foundation

    The dbt Cloud / Snowflake platform that became Canlin’s foundation for operational data, BI, and ML — automation from it saved 50+ hours per week across Operations. Read more

  5. 2022–2024

    8,000-well forecastingdaily production ML

    Modified XGBoost models forecasting the next 30 days of production for 8,000+ wells, inferring daily into corporate reporting — plus 2-year forecasts across the full well set. Read more

  6. 2022–2024

    IROC analyticsremote operations centre

    Real-time well status and production dashboards for Canlin’s Integrated Remote Operating Centre, with facility-outage impact auto-assessment built on networkx.

  7. 2023–now

    Claude Code toolchainskills · sub-agents · hooks · MCP

    A cross-repo AI-native development practice: custom skills, sub-agents, hooks, and MCP servers — including profiling my own agent usage to find where the time was actually going, then promoting the dominant pattern into a first-class sub-agent.

  8. 2024–2025

    Auto-Frac sequenceroptimization app

    Streamlit app replacing a manual operations-scheduling task with a purpose-built optimization algorithm balancing efficiency, sequencing, and equipment-rotation constraints.

  9. 2024–2025

    Modern-stack PoCPython · dbt · cube.js · DuckDB

    A fully-working local modern data stack (Python ingestion → dbt Core → cube.js → DuckDB → PowerBI, in Docker) that replaced legacy R + CSV flows and anchored the case for cloud analytics.

  10. 2025–now

    US Dagster platform300M+ records · 945 assets

    Production-grade Dagster-native platform for US oil & gas data: Polars/DuckDB performance layer, Terraform-managed AWS, schema contracts, and CI — the case study in shipping a modern data platform AI-first. Read more

What it adds up to

  • Data platform engineering

    Dagster, dbt, Snowflake, Polars, DuckDB — three generations of platform builds, each one the foundation its company still runs on.

  • ML & AI engineering

    LLM-in-the-loop pipelines, structured outputs, MCP servers and Claude Code toolchains on the AI side, and forecasting, classification and anomaly detection actually deployed on the ML side — 8,000 wells inferring daily into corporate reporting, not notebooks.

  • Analytics engineering & BI

    Tableau and PowerBI as corporate platforms rather than one-off dashboards, semantic layers over the warehouse, and reporting automated end to end — the weekly production report alone gave Operations back 50+ hours a week.

  • Data leadership

    Team coordination, mentorship, and board-level ownership — currently a 6-person cross-border team, with a decade of turning analysts into data professionals behind it.

Live preview of Twochannel's system builder — a flagship AI-native monorepo designed and built end-to-end.

How I work

My Red Bull Wingfinder profile puts Autonomous and Reserved at the far end, with Achiever and Dutiful right behind, which reads about right: I do my best work with room to think and a standard of my own to hit, and I tend to see things through. Hover any scale for the detail.

Connections

how you manage relationships, and how well you work independently

Drive

level of ambition

Creativity

how original the thinking is, against how logical and analytical

Thinking

what you draw on when solving problems

Red Bull Wingfinder ↗ · 12 bipolar scales across 4 areas · completed 18 Aug 2026 · filled bars are the four flagged top strengths

Hiring for a data or AI team?

The fastest way to reach me is email — or the resume is one click away.