Engineer · Data · Automation · AI
About
I’m Luis Faria, a software and data engineer based in Sydney. For 10+ years I’ve built systems that turn manual, messy processes into automated, measurable products - across healthcare, marketing agencies, and tech.
I led technical projects and delivered custom ERP/CRM platforms for a 20+ clinic healthcare group serving 1M+ client records, then built Konquista, a Django + Celery/Redis automation platform pushing 30K+ WhatsApp messages a month across clinics. After relocating to Sydney, I moved deeper into data and software engineering.
Today I build data systems at St Catherine’s School, Sydney - SQL Server pipelines and Power BI reporting that give staff reliable, decision-ready numbers in a regulated educational environment.
I’m completing a Master of Software Engineering with AI, and I keep the learning applied: secure cloud architectures on AWS, a self-hosted Apache Superset BI deployment, applied machine learning (scikit-learn, CRISP-DM), and LLM tooling on OpenAI and Claude. I build in public - shipping, writing, and sharing the wins and the scars.
Sydney, Australia
Currently
Building data systems at St Catherine’s School, Sydney - SQL Server pipelines and Power BI reporting - while completing a Master of Software Engineering with AI. I keep the coursework applied: secure cloud architectures on AWS, a self-hosted Apache Superset BI deployment, applied machine learning (scikit-learn, CRISP-DM, Spark), and LLM tooling on OpenAI and Claude - much of it open-sourced in my Master’s repo (1,100+ commits, mostly Jupyter notebooks).
What I do
Software Engineering
Full-stack products shipped end-to-end - most recently a pentested portal serving 2,000 parents, built solo in 8 weeks.
Data Engineering
Pipelines, reporting and BI people trust - from reverse-engineering legacy ETL estates to dashboards leadership actually uses.
Automation & DevOps
I find manual work and delete it - a 100-minute batch job cut to ~2 seconds; deploy downtime from 10+ minutes to ~2s.
AI / ML
Applied ML with honest metrics - deployed scikit-learn services, RAG assistants, and a 1,100+ commit open-source agentic pipeline.
Tools I work with
Software
Data
Automation & DevOps
AI / ML