Somewhere sensible to keep your data

Selected work demonstrating this service.

• 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.

• Ran 100 PostgreSQL, MS SQL, BigQuery warehouses

  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.

• A maritime platform built in clean layers

  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 from Postgres to API

  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 function‑first PostgreSQL data layer

  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.

• Quicker answers from a better choice of key

  Adopted UUID v7 time‑ordered identifiers (PostgreSQL 18) as entity keys to reduce B‑tree index fragmentation and speed up queries.

• Implemented a catalogue‑driven deep‑merge

  Implemented a catalogue‑driven deep‑merge for stored JSON preferences, preventing missing‑key crashes as the schema evolves.

• Modeled 348 tables across 34 Postgres schemas

  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 Stripe and in‑app purchase entitlements

  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 onto a River job queue

  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 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.

• Built a loyalty wallet, leagues and badges

  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 and seafarer career workspaces

  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.

• Built a database‑driven CV generator

  Built a database‑driven CV, references, portfolio and cover‑letter generator in Python — 41 modules, 10,580 lines — rendering six output formats from one 23‑table SQLite source assembled by a 19‑step idempotent pipeline.