# Performance Tuning > Selected Engineer ApS work demonstrating Performance Tuning — the achievements that prove it. - [Engineered hourly electricity consumption aggregation pipeline in Python / SQL / Bash + Jq, achieving 180ms for 30‑day datasets across heterogeneous JSONL sources.](https://data.engineer.company/portfolio/engineered-hourly-electricity-consumption-aggregation-pipeline-in-python-4/) - [Accelerated geographical data pipeline performance by 50x by improving SQL programming and data modeling across PostgreSQL, MS SQL, and Google Cloud BigQuery.](https://data.engineer.company/portfolio/accelerated-geographical-data-pipeline-performance-by-50x-by-5/) - [Improved geographical map application performance by 10x through strategic database transition from MSSQL to PostgreSQL, optimizing processing and data security.](https://data.engineer.company/portfolio/improved-geographical-map-application-performance-by-10x-through-6/) - [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.](https://data.engineer.company/portfolio/resolved-1-000-issues-in-geographical-data-and-7/) - [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.](https://data.engineer.company/portfolio/architected-created-and-managed-100-postgresql-ms-sql-12/) - [Designed, deployed, and maintained 10 PostgreSQL and MS SQL servers on Ubuntu Linux VPS, ensuring optimal server performance and reliability.](https://data.engineer.company/portfolio/designed-deployed-and-maintained-10-postgresql-and-ms-13/) - [Accelerated PostgreSQL performance by 10x via strategic indexing, partitioning, and query optimization, enhancing database efficiency for user, tenant, geospatial, and time‑series electrical data.](https://data.engineer.company/portfolio/accelerated-postgresql-performance-by-10x-via-strategic-indexing-15/) - [Engineered 600 PL/pgSQL‑based ETL/ELT pipelines to streamline complex data processing workflows across multiple PostgreSQL development and production environments.](https://data.engineer.company/portfolio/engineered-600-pl-pgsql-based-etl-elt-pipelines-54/) - [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.](https://data.engineer.company/portfolio/designed-a-json-passthrough-architecture-where-postgresql-functions-58/) - [Adopted UUID v7 time‑ordered identifiers (PostgreSQL 18) as entity keys to reduce B‑tree index fragmentation and speed up queries.](https://data.engineer.company/portfolio/adopted-uuid-v7-time-ordered-identifiers-postgresql-18-64/) - [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.](https://data.engineer.company/portfolio/modeled-the-maritime-domain-professionals-companies-ships-jobs-67/) - [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.](https://data.engineer.company/portfolio/moved-slow-work-onto-a-river-job-queue-97/) - [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.](https://data.engineer.company/portfolio/built-first-party-product-analytics-in-postgresql-101/) - [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.](https://data.engineer.company/portfolio/built-the-loyalty-and-reputation-system-105/)