Getting your data from A to B on its own

Selected work demonstrating this service.

• One infrastructure plan for 14 departments

  Designed a comprehensive infrastructure framework for a research institute impacting 14 departments, featuring flexible modules, unified data pipelines, and structured support strategies for long‑term adoption.

• A month of meter readings in 180 milliseconds

  Engineered hourly electricity consumption aggregation pipeline in Python / SQL / Bash + Jq, achieving 180ms for 30‑day datasets across heterogeneous JSONL sources.

• Made a geographical data pipeline 50x faster

  Accelerated geographical data pipeline performance by 50x by improving SQL programming and data modeling across PostgreSQL, MS SQL, and Google Cloud BigQuery.

• Resolved 1,000 issues in geographical data

  Resolved 1,000 issues in geographical data and time‑series data, using GDAL, ArcGIS, PostGIS, Mapbox, QGIS, SQL (PL/pgSQL, Transact‑SQL), Bash, ensuring high‑quality big data processing.

• Designed and ran 6 ETL/ELT pipelines

  Designed, implemented, and administered 6 ETL/ELT pipelines, utilizing Google BigQuery, MSSQL, PostgreSQL, Shell scripting, PL/pgSQL, and Transact‑SQL, integrating data for efficient Python API processing.

• Automated GIS SaaS deployment with GitHub Actions

  Automated GIS SaaS application deployment, data processing, and reporting system using GitHub Actions CI/CD, Python, Bash, and SQL.

• Automated delivery of 20 GIS data pipelines

  Automated delivery of 20 GIS data pipelines and app data ETL processes, streamlining infrastructure automation and reporting.

• Led 30+ GIS projects from build to support

  Led the development, deployment, and support of over 30 GIS projects, demonstrating expertise in PostgreSQL, Bash, Python, JavaScript, GDAL, ArcGIS, PostGIS, and Mapbox technologies.

• Saved 4,000 hours with GitHub and GitLab CI/CD

  Streamlined data analysis and software development processes, saving 4,000 hours by introducing GitHub, GitLab, Bash, and Python CI/CD practices.

• Automated data processing in Python and PL/pgSQL

  Automated data processing tasks using Shell scripting, PL/pgSQL, Python, and Transact‑SQL, increasing productivity and efficiency.

• Engineered 600 PL/pgSQL ETL/ELT pipelines

  Engineered 600 PL/pgSQL‑based ETL/ELT pipelines to streamline complex data processing workflows across multiple PostgreSQL development and production environments.

• A mapping product, carried end to end

  Architected, developed, implemented, supported infrastructure, data processing, and the map application for 2 years non‑stop without any weekends, holidays, or vacations, 10–14 hours a day.

• Built first‑party analytics inside PostgreSQL

  Built first‑party product analytics in PostgreSQL — 47 functions over partitioned event tables that prune themselves — pseudonymised behind a rotating salt and gated on the visitor's consent.

• Generated 495 pages from a SQLite export

  Generated 495 achievement pages across three languages from a read‑only SQLite export, with the page address authored as data so that correcting a sentence no longer moved the page and broke the link.