What I build, and why it actually matters for your business
Here is the thing about automation and data work: nobody wakes up excited about ETL pipelines or webhook architecture. What people care about is the result. Fewer hours lost to manual work. Leads that do not slip through the cracks. Reports that show up on time without someone staying late to build them.
So here is what I build, organized by the actual problem each one solves.
Data pipelines and ETL
The problem
Your data lives in five different places, and getting it into one usable format means someone exporting CSVs, copy-pasting into spreadsheets, and praying nothing breaks.
What I build
Reliable pipelines that pull data from wherever it lives, whether that is Bloomberg feeds, SQL databases, SaaS APIs, or shared network drives, clean it up, and land it exactly where it needs to be. No more manual exports. No more "wait, is this number even current."
In practice
At OMERS, I built pipelines handling live financial data from Bloomberg SAPI and MSCI APIs into PostgreSQL, used daily by risk and portfolio management teams.
Have a data mess you have been avoiding?Tell me what's going on and I will tell you what it would take to fix it.
Leads come in faster than your team can manually review them, and by the time someone gets to a hot lead, it has gone cold.
What I build
AI systems using OpenAI and Claude that read incoming leads, score them against your specific criteria, and route them automatically to the right person. Chatbots that handle real conversations, not just canned FAQ responses, and know when to bring in a human.
In practice
For a marketing agency client, I built an end-to-end system that captures leads, scores them with AI, nurtures the ones that are not ready yet, and books appointments automatically once a lead qualifies. The team only handles the conversations that actually need them.
Curious what AI-driven lead qualification could do for your pipeline?Let's talk through it.
Someone on your team spends hours every week doing the same repetitive task: pulling reports, updating spreadsheets, sending the same follow-up emails.
What I build
Automations using n8n and Python that handle the repetitive work permanently. Triggers based on events, schedules, or incoming data, with proper error handling so the automation does not silently fail at the worst possible time.
In practice
One client's team was spending over 25 hours a week manually pulling campaign data and writing client reports. The automated version runs overnight and lands in the client's inbox every morning, no human required.
What's eating your team's time right now?Describe it here and I will tell you honestly if automation is the answer.
Your systems either do not scale, or they scale and the bill becomes a monthly surprise.
What I build
Cloud architecture on AWS, GCP, or Azure designed for your actual stage and budget, whether that is serverless functions for a lean startup or containerized infrastructure for something more established. Plus dashboards in Streamlit or React that actually get used, because they are built for the people looking at them daily, not for a one-time demo.
Wondering if your current setup is costing you more than it should?Ask me directly.