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Title Line

Product Manager, Stack Maps & Public Data | Stack Technologies Ltd. | May 2026 - Present

Role Summary

Stepped into a Product Manager role spanning the Stack Maps product (frontend + API) and the broader Public Data team — managing and planning the roadmap for a 5-person group across two countries. Driving Stack Maps direction across frontend, API, and data, while the team runs the Canadian data pipelines and continues to mature the US Dagster platform. Built on the engineering foundation of the prior Data Platform Engineer role; now shaping where the product goes next.

Key Achievements (Bullets)

- Driving the Stack Maps roadmap across frontend and API — prioritizing and shipping features alongside the dedicated frontend and generalist engineers.
- Leading 5 engineers (1 frontend, 1 API/generalist, 3 early-career data engineers) across US and Canadian public-data codebases — coaching, code review, and a unified roadmap.
- Aligning the US and Canadian public-data codebases — shared patterns where they pay off, regional autonomy where they don't.
- Player-coach: still shipping in Dagster and Stack Maps; the AI-native Claude Code toolchain that powered the IC role now multiplies team output.

Detailed Highlights (with categories)

Stack Maps product direction:
- Driving the Stack Maps roadmap across frontend and API — prioritizing and shipping features alongside the dedicated frontend and generalist engineers.
Leading the Public Data team:
- Leading 5 engineers (1 frontend, 1 API/generalist, 3 early-career data engineers) across US and Canadian public-data codebases — coaching, code review, and a unified roadmap.
- Aligning the US and Canadian public-data codebases — shared patterns where they pay off, regional autonomy where they don't.
Player-coach engineering:
- Player-coach: still shipping in Dagster and Stack Maps; the AI-native Claude Code toolchain that powered the IC role now multiplies team output.

Full Description (Summary + Achievements)

Stepped into a Product Manager role spanning the Stack Maps product (frontend + API) and the broader Public Data team — managing and planning the roadmap for a 5-person group across two countries. Driving Stack Maps direction across frontend, API, and data, while the team runs the Canadian data pipelines and continues to mature the US Dagster platform. Built on the engineering foundation of the prior Data Platform Engineer role; now shaping where the product goes next.

- Driving the Stack Maps roadmap across frontend and API — prioritizing and shipping features alongside the dedicated frontend and generalist engineers.
- Leading 5 engineers (1 frontend, 1 API/generalist, 3 early-career data engineers) across US and Canadian public-data codebases — coaching, code review, and a unified roadmap.
- Aligning the US and Canadian public-data codebases — shared patterns where they pay off, regional autonomy where they don't.
- Player-coach: still shipping in Dagster and Stack Maps; the AI-native Claude Code toolchain that powered the IC role now multiplies team output.

Education Snippets

Skills Summary

All Skills (Grouped by Type)

Data & Software:
- 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, Prompt caching & evals, RAG, Agent frameworks (autogen, crew), 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, TensorFlow / Keras, Hugging Face, nltk, Time-series forecasting, Classification, Anomaly detection
- Databases: Snowflake, PostgreSQL, DuckDB, Neo4j, networkX, MongoDB, SQL Server, Oracle, Hive
- 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:
- Programming Languages: Python, SQL, TypeScript, JavaScript, Bash, R

Oil & Gas:
- Upstream Oil & Gas: Exploitation / Development Engineering, Production Engineering, Operations, Corporate reporting, A&D evaluation
- Petroleum Reserves Evaluation: COGEH, NI 51-101