Matthew Nelson
AI-native Data Platform Engineer · Berkeley MIDS · P.Eng
Calgary, Alberta · matthewpeternelson@gmail.com · +1-403-667-3022 · https://mnelson.ca · Github: https://github.com/matthewpnelson · LinkedIn: https://linkedin.com/in/matthewpeternelson
Data platform engineer and AI-native builder. 10 years in data, 16 in engineering, Berkeley MIDS and P.Eng. I build production data platforms on Dagster, Snowflake, Polars, DuckDB and dbt. I then ship AI-native systems on top of them. These are LLM-in-the-loop pipelines, traced tool-loop agents with evals, and agentic developer tooling with Claude Code and MCP. I rebuilt StackDX's US data platform as lead engineer. I now run the roadmap and code review for the 6-person team, and still ship weekly.
Selected Impact
- Architected StackDX's production Dagster platform across 15 US states and 945 transformation assets. It distills a 3.8 TB source layer into a 10.3 GB layer serving 300M+ records.
- Founded twochannel.ai, an AI-native catalog of 18k+ products across 2k+ brands. LLM-in-the-loop pipelines and a Claude Code toolchain maintain it, with one engineer end to end.
- Owned Canlin's regulated annual reserves evaluation for 5 years. This externally-audited valuation feeds the financial statements, and technical revisions added +$730M (NPV10).
- Built the dbt Cloud / Snowflake platform that became Canlin's foundation for operational data, BI and ML. Automation from it saved 50+ hours/week across Operations.
- Set the roadmap and review code for a 6-person, two-country data team at StackDX. Still ship weekly in the platform codebases.
Experience
Product Manager, Stack Maps & Public Data · Stack Technologies Ltd.
May 2026 — Presentwww.stackdx.com/
Moved from lead engineer into product ownership after the US data platform rebuild. I run the roadmap and code review for a 6-person team across two countries. I still ship weekly in the Dagster and Stack Maps codebases.
Product ownership and team leadership
- Run the roadmap, priorities and code review for a 6-person team across the US and Canadian data codebases. Still ship in the Dagster platform each week.
- Built the PM tooling as software, in daily use. It includes a Jira roadmap scheduler, human-gated triage of production failures, and skills for weekly updates.
- Set Stack Maps product direction. Prototyped the forecast and type curve feature and the new US well-details pane, now landing with minor changes.
Still shipping on the US platform
- Designed the US well-detail data model as six panel exposures keyed on api10/api12/api14. Production rolls up from the filed grain and loads to Redshift by state-partitioned COPY.
- Wrote the decline engine for the forecasting app. It fits deterministic bounded Arps curves per well and phase, with EUR and fit diagnostics, monthly in Dagster.
- Added Mississippi as the sixteenth state in three days. The data covers wells, production back to 1980, permits from 1997 and well dates.
Data Platform Engineer · Stack Technologies Ltd.
Jun 2025 — May 2026www.stackdx.com/
Lead engineer on the USA data platform rebuild. I replaced a legacy Python ETL stack with a production-grade Dagster-native architecture on AWS. Polars and DuckDB do the heavy transformation work. The platform distills a 3.8 TB source layer of 1.03M regulator files into a 10.3 GB exposure layer. That layer serves 127M well production records, 172M lease production records and 4.1M wellheaders to customer endpoints. I built it AI-first, on custom Claude Code skills and hooks for scaffolding, formatting and review.
Modern Data Platform Architecture
- Architected a production Dagster platform across 15 US states and 945 assets. It distills a 3.8 TB source layer into a 10.3 GB layer serving 300M+ records.
- Stopped a repeat production out-of-memory failure. Converted the Texas production fact build, the largest on the platform, to a streaming Polars plan.
- Designed 146 contract-driven freshness checks that fan out to 468 evaluations across all 15 states. Calibrated the thresholds to stop false-positive alerts.
- Designed reusable exposure and coalesce patterns. Legacy mart schemas run on the new fact tables, and a new state extends the pattern without a bespoke build.
AI-native Developer Workflow
- Built a project Claude Code toolchain: an auto-format hook and skills for pipeline triage, exposure coverage and schema work. My token-optimization layer has saved 655M tokens across projects.
Cloud Infrastructure & DevOps
- Deployed the AWS footprint with Terraform across staging and production. It is RDS, S3 and ECS compute that Dagster launches and manages per job.
- Implemented CI/CD on GitHub Actions with ruff, pyright and asset schema-contract tests. Automated the branching and deployment behind staging-to-production releases.
Framework & Team Enablement
- Implemented 10 of 15 state pipelines solo. Two non-platform engineers then shipped the rest from the documented conventions and schema contracts.
Founder & Principal Engineer · Twochannel
Jan 2021 — Presenttwochannel.ai
Designed and built Twochannel end to end: catalog, ingestion pipelines, search, recommendations and frontend. I rebuilt it three times since 2021 as the stack evolved, and launched it publicly in 2026. AI-native workflows maintain almost all of the 18k+ product / 2k+ brand catalog. These are LLM-in-the-loop scrapers, structured-output enrichment, semantic dedup and a Claude Code toolchain over the full monorepo. A catalog this size normally needs a small data team, and it's just me.
AI-assisted product catalog at scale
- A brand-scraper, LLM normalizer and reviewed dedup pipeline maintains 18k+ products across 2k+ brands in Directus. It needs minimal manual work.
- Shipped a 14-tool member assistant with every turn traced to Langfuse. A 6-suite, 4-model eval bake-off picked the model and caught it inventing product ids.
- Replaced a 12-agent Claude Code curation team with a judged pipeline of 7 decision types. Haiku escalates to Sonnet, writes can be undone, and rollout is shadow-first.
- A wizard captures budget, room and genres. An async build job returns complete system variants within signal-chain adjacency and per-category budget limits.
Platform Architecture
- Built a Turborepo monorepo across three hosting targets. It ships Next.js on Vercel, Directus on Railway, Algolia search, Neo4j relationships and Doppler-managed secrets.
- Shipped GDPR Article 17 erasure: a twelve-step deletion pipeline with audit trail, CI-enforced FK rules and weekly orphan sweep. An 86-test Playwright E2E suite backs it.
Senior Data Analytics Engineer · Paramount Resources Limited
Apr 2024 — May 2025paramountres.com
Senior member of the Data Analytics and Integration team. I brought best practices across the full data stack, mentored ICs and advocated for a modern data platform. I delivered custom web apps, modern data-stack PoCs, data engineering pipelines and high-fidelity dashboards. Toolkit: Databricks, PowerBI, Spotfire, dbt Core, cube.js, DuckDB; SQL, Python, R, DAX.
Dashboards & Corporate Reporting
- Built the corporate PowerBI dashboard suite for Netback, Operating Cost and Capital. Executives, operations, production engineering and development use its corporate-to-well drill-downs.
- Automated the weekly well production report end to end with Spotfire and Power Automate. This removed a half-day manual task from the analytics manager each week.
Custom Web Applications
- Replaced a manual 2–3-hour Excel frac-scheduling process with a Streamlit optimization app. Its sequence plans ran ~8 multi-well pads.
Data Governance & Platform Advocacy
- Built a local modern data stack PoC in Docker to replace legacy R and CSV processes. The stack was Python, dbt, cube.js, DuckDB and PowerBI.
- Advocated for cloud-first analytics on the data governance committee. Educated senior leadership on modern stack design.
Data & Advanced Analytics Lead · Canlin Energy Corporation
Feb 2022 — Apr 2024canlinenergy.com/
Designed, built and ran Canlin's modern data stack: dbt Cloud, Snowflake, DataRobot, Tableau and Streamlit. I led the analytics for the Integrated Remote Operating Centre (IROC). I owned descriptive and predictive solutions end to end and mentored junior professionals into data roles. I made the business case to senior leadership for sustained investment in analytics.
Corporate Data Warehouse on dbt Cloud + Snowflake
- Built the dbt Cloud / Snowflake platform that became Canlin's foundation for operational data, BI and ML. It gave one source of truth from SCADA to Accounting.
- Saved 50+ hours/week across Operations. Automated the weekly production reporting process end to end: backend workflows, input sheets and the report itself.
Data Science & ML Ops
- Deployed a modified XGBoost forecaster that infers daily across 8,000+ wells on a 30-day horizon. It also feeds 2-year forecasts of the full well set to corporate reporting.
- Built the real-time well-status analytics behind Canlin's remote operations centre (~500 wells). It includes networkx-based outage impact assessment and anomaly-detection reporting.
- Built a Streamlit SME-labeling app and a classification model. The model ranks well risk across the portfolio, with explanations.
- Built a home-grown ML-ops layer on Streamlit, Snowflake and NocoDB for labeling and data input. DataRobot ran the productionized models.
Corporate Data Scientist & Reserves Manager · Canlin Energy Corporation
Oct 2017 — Jan 2022canlinenergy.com/
Drove Canlin's transition to a self-service data model by pairing data engineering with petroleum-data expertise. I implemented Tableau as the company-wide reporting tool and data mart. I advocated for repeatable BI, advanced analytics and automation. I owned the regulated annual reserves evaluation, the externally-audited valuation of every corporate asset. It ties directly to the financial statements. Technical revisions improved its accuracy and added +$730M in value.
Tableau data-warehouse implementation
- Implemented Tableau as the corporate reporting platform. Published 100+ data sources, 50 workbooks and 20 Prep flows in year one.
- Mentored every Tableau Creator and Explorer in the company. Made the executive case for self-service data.
Corporate Reserves — regulated annual asset valuation, 5 years
- Owned the externally-audited NI 51-101 reserves evaluation for 5 years. Technical revisions added +$730M (NPV10) across four consecutive cycles.
Corporate Acquisitions & Divestitures
- Built the data flows and dashboards for rapid A&D evaluation. The divestiture cycle, at depressed prices, took corporate debt from $120M to $0.
Exploitation / Development Engineer, Foothills & South · Centrica Energy Canada
Jul 2014 — Sep 2017www.centrica.com/
Exploitation and development engineering across multiple assets. I authored the multi-scenario asset-longevity analysis that set the 5–10-year corporate strategic direction.
Asset-longevity analysis & internal tooling
- Modeled asset longevity across all operated facilities in multiple scenarios. The analysis set the 5–10-year corporate strategic direction.
- Built a VBA opportunity-tracking tool with a staging and approval workflow for development planning.
Production & Exploitation Engineer · Pengrowth Energy
Aug 2010 — Jun 2014On-site production engineering plus exploitation engineering across multiple assets. I built multi-dimensional tracking models from time-series sensor data and designed data-driven drill programs.
Highlights across both roles
- On-site production and operations engineering, with long-term sensor-data trending and equipment monitoring.
- Built multi-dimensional tracking models from time-series thermocouple sensor data.
- Designed drill programs and ran feasibility analysis across multiple assets.
Engineering Co-op Student · Pengrowth Energy (Co-op)
2006 — 2010Multiple co-op terms in the University of Waterloo Engineering program. These were 8 months at Lanmark Engineering, 4 months at the Olds Sour Gas Plant and 12 months at Pengrowth. The Pengrowth term was an Exploitation Engineering co-op in the office.
Selected Projects
twochannel.ai · twochannel.ai
2021 — CurrentAI-assisted HiFi product catalog and intelligent stereo-system designer. Founder project; see the Twochannel entry under Experience for the full detail. LLM-augmented ingestion, semantic dedup and a Claude-Code-first developer workflow maintain 18k+ products across 2k+ brands. Stack: Next.js, Directus, Algolia, Neo4j, Turborepo.
- AI-native monorepo developed primarily through Claude Code (skills, sub-agents, hooks, MCP)
- LLM-in-the-loop ingestion + human-reviewed semantic dedup
- Next.js frontend on Vercel, Directus CMS on Railway, Algolia search, Neo4j relationships
- Doppler single-source-of-truth secret management across Vercel / Railway / GitHub Actions
- 86-test Playwright E2E suite
StackDX USA Data Platform · www.stackdx.com
2025 — CurrentProduction-grade USA oil & gas data platform at StackDX. It has Dagster-native orchestration and transformations, a Polars/DuckDB performance layer and Terraform-managed AWS infra. I developed it AI-first with a purpose-built Claude Code toolchain. The toolchain is task skills for pipeline triage, exposure coverage and schema work, plus an auto-format hook.
- 15 US states, 945 Dagster transformation assets, 300M+ served records
- Targeted Polars + DuckDB rewrites and incremental materializations cutting processing time on critical datasets
- Reusable exposure/coalesce-sources patterns for legacy-schema compatibility
- AWS infra-as-code (RDS, ECS, S3) with Terraform
- Custom Claude Code skills and hooks driving developer velocity
Instill · instillmeditation.ca
2017 — 2018A modern and refined meditation and lifestyle brand. The site remains active. The bulk of the build ran 2017–2018 as a full-stack React app for online course content.
Vedic Meditation Directory · learnvedicmeditation.co
2018 — 2019Helped students find their local teacher of Vedic Meditation. It ran through multiple versions, from a full-stack React app down to a simple Next.js static site. A single Google Doc powers the final version, so teachers manage their own listings.
Skills
AI Engineering & Agentic Development: Claude Code (agents, skills, hooks, slash commands, sub-agents), MCP servers & clients, Anthropic / OpenAI / Perplexity APIs, Vercel AI SDK, Structured outputs & schema-adherent LLM calls, Tool-loop agents with scope and grounding guards, Evals & model bake-offs, Langfuse / OpenTelemetry tracing, Prompt caching, RAG, LLM-in-the-loop data pipelines, Editors: Claude Code, Cursor, Windsurf
Data Engineering & Modern Data Stack: dbt (Core & Cloud), Dagster, Snowflake, Snowpark, Polars, DuckDB, Tableau Prep, cube.js & dbt semantic layers, pandas, SQL, Schema contracts
Cloud, Infra & DevOps: AWS (ECS, RDS, S3), Terraform, Docker, GitHub Actions CI/CD, Vercel, Railway, Supabase, Doppler, pre-commit / ruff / pyright
Data Visualization & BI: Tableau, PowerBI, Spotfire, Plotly, D3.js, matplotlib, Seaborn, Dash, Bokeh, ggplot2
Machine Learning & NLP: scikit-learn, XGBoost, PyTorch, Hugging Face, nltk, Time-series forecasting, Classification, Anomaly detection
Databases: Snowflake, PostgreSQL, DuckDB, Neo4j, networkX, MongoDB, SQL Server, Oracle
Web App Development: Next.js, React, Astro, Directus (headless CMS), Algolia, Node.js, Express, Tailwind CSS, Playwright, Streamlit, Flask, Dash, Turborepo / npm workspaces
ML Ops: Snowflake & Snowpark, DataRobot, Streamlit labeling apps, Active learning workflows
Programming Languages: Python, SQL, TypeScript, JavaScript, Bash, R
Upstream Oil & Gas: Exploitation / Development Engineering, Production Engineering, Operations, Corporate reporting, A&D evaluation
Petroleum Reserves Evaluation: COGEH, NI 51-101
Education
Master of Information and Data Science · University of California, Berkeley
May 2016 — Jun 2018 · GPA 3.888Bachelor of Applied Science, Chemical Engineering · University of Waterloo
Sep 2005 — Jun 2010Certifications
- Professional Engineering Designation (P.Eng) — Association of Professional Engineers and Geoscientists of Alberta (APEGA) (2014)
Awards
- Randy Duxbury Memorial Award — University of Waterloo (2010)
- Ontario International Education Opportunity Scholarship — University of Waterloo (2007)