IDEAS • DATA • PRODUCTS

Turning ideasinto useful solutions.

I analyze needs, structure data and build digital products that turn ideas into usable solutions.

Pipelines • SQL • Automation

Structure. Connect.Secure.

I build the pipelines, SQL models, and automation workflows that turn fragmented sources into clean, structured, and ready-to-analyze data.

Cotonou, BeninScroll to explore01 — 04
Georgeo Agbahungba

Who I am

About Me

The whole data chain, from field to dashboard

ETL PipelinesSQL & ModelingCloud & Quality

I am Georgeo AGBAHUNGBA, a data engineer. I design the systems that make data trustworthy, from field collection through to reporting.

My original ground is agricultural: surveys, value chains, monitoring and evaluation. That is where I learned that badly collected data can never be repaired downstream.

I build ETL pipelines, SQL models, and automated quality controls. The goal is not the dashboard, it is how much you can trust it.

I work with Python, SQL, Supabase, and cloud infrastructure, bringing in generative AI where it saves time without costing reliability.

Technical stack

One chain, tooled end to end.

Collect, clean, model, automate, report: every stage in the life of a dataset has its tools, and I hold the whole chain rather than one link.

Data Engineering & Cloud

  • Python
  • SQL
  • Supabase
  • Google Cloud
  • AWS Cloud
  • APIs
  • Data Pipelines (ETL)
  • Generative AI / LLMs

My Way of Working

Problem first.

Solution second.

Trustworthy before readable.

Data is only worth what it can be trusted for. I start with quality and traceability, long before any dashboard.

Projects & Products

Problems turned into products.

I build the pipelines, SQL models, and automation workflows that turn fragmented sources into clean, structured, and ready-to-analyze data.

Explore all projects

My Journey

One career.
Multiple perspectives.

Agroeconomics, development, Data Engineering: select the version of my career path that best matches your target context.

01

Data Engineering

Collection · ETL · SQL · Quality · Decision

Agricultural data life cycle: survey design, quality control, modeling, and output presentation.

Your data deserves better than a spreadsheet.

The source.
The pipeline.
The decision.

Data scattered across sources, field collection that needs to become reliable, indicators you cannot recompute from one month to the next: tell me the situation. We will start from there.