PostgreSQL

• Accelerated geographical data pipeline performance by 50x by improving SQL programming and data modeling across PostgreSQL, MS SQL, and Google Cloud BigQuery.
• Improved geographical map application performance by 10x through strategic database transition from MSSQL to PostgreSQL, optimizing processing and data security.
• 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, 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.
• Released 500 electricity and GIS data analysis reports, utilizing deep research and troubleshooting to ensure accurate geographic and time series big data insights.
• Architected, created, and managed 100 PostgreSQL, MS SQL, and Google BigQuery data warehouse databases with primarily GIS and time‑series data, optimizing performance and scalability.
• Directed full‑stack GIS map development, overseeing PostgreSQL, Mapbox, ReactJS, and NodeJS to deliver an integrated solution.
• Led the development, deployment, and support of over 30 GIS projects, demonstrating expertise in PostgreSQL, Bash, Python, JavaScript, GDAL, ArcGIS, PostGIS, and Mapbox technologies.
• Architected a layered maritime platform separating a Next.js PWA frontend, a Go (Huma/Fiber) API, and a PostgreSQL function layer, keeping all business logic in the database.
• Designed a JSON passthrough architecture where PostgreSQL functions return complete JSON forwarded verbatim by the Go API, eliminating intermediate unmarshalling and decoupling the frontend from schema changes.
• Designed a PostgreSQL function‑first data layer — 1,275 stored functions across 34 schemas — so every read and write goes through a function the database can grant, rather than through a table.
• Implemented a catalogue‑driven deep‑merge for stored JSON preferences, preventing missing‑key crashes as the schema evolves.
• Modeled the maritime domain into 348 normalized tables across 34 PostgreSQL schemas — professionals, companies, ships, jobs, reviews and the rest — with SMALLINT lookups and UUID v7 keys.
• Built a layered automated test suite — 981 Go tests, 543 frontend and browser specs, 494 SQL behavioural tests — with mutation testing, property‑based tests and an accessibility gate.
• Built the payments and entitlements layer — Stripe alongside Apple and Google in‑app purchase — gating the directory, search and export through an 11‑table access model checked on the server.
• Moved slow work off the request path onto a River job queue — 15 worker modules, 8 scheduled tasks and 20 pg_cron jobs — so a request returns while the work behind it carries on.
• Built the loyalty and reputation system — 67 functions over a 31‑table ledger, with leagues, badges and a redemption shop — taking a row lock on the balance to close the double‑spend window.
• Built the hiring marketplace and the seafarer career workspace — 151 stored functions across 48 tables — covering vacancies, applications, certificates, rank progression and verified sea time.

This work is part of what we offer as Backend & API Development, Database Design & Modeling, GIS & Geospatial Solutions, Data Governance & Quality, Data Pipeline Development (ETL/ELT), Full‑Stack Product Development, Platform & Solution Architecture and Data Warehouse Design.

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