Data Governance

10 Achievements

Designed a comprehensive infrastructure framework for DTU impacting 14 departments, featuring flexible modules, unified data pipelines, and structured support strategies for long‑term adoption.
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 and time‑series data, using GDAL, ArcGIS, PostGIS, Mapbox, QGIS, SQL (PL/pgSQL, Transact‑SQL), Bash, ensuring high‑quality big data 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.
Gathered and analyzed business requirements to translate into actionable features and user stories aligned with data governance standards.
Engineered 600 PL/pgSQL‑based ETL/ELT pipelines to streamline complex data processing workflows across multiple PostgreSQL development and production environments.
Designed a PostgreSQL function‑first data layer across the platform's domain schemas (identity, organization, review, message, notification and more), exposing all data access through stored functions.
Implemented a catalogue‑driven deep‑merge for stored JSON preferences, preventing missing‑key crashes as the schema evolves.
Modeled the maritime domain — professionals, companies, ships, jobs and reviews — into normalized PostgreSQL schemas with SMALLINT lookups and UUID v7 keys.