Gabriel Borda

I'm a data engineer with four years of experience, currently at Serasa Experian, part of Experian plc. I got here through an unusual route: I trained as an environmental engineer at UFV, spent a few years in sales — including leading a team at Stone and building a sales operation from scratch at a small energy company — then taught myself Python and moved into data in 2022.

My first data role was at Agrosatélite, a geotechnology company, where I was the only data analyst. I owned everything data-related: automated the collection routines with Python and Selenium after inheriting a pile of scripts that had to be run by hand, maintained the geospatial datasets the analysis teams depended on, and deployed an internal GeoNode platform to centralize the company's map layers. Agrosatélite was acquired by Serasa Experian in 2023, I was retained, and I moved into the data engineering team.

Today I run the ETL platform behind my business unit's agribusiness products: around 200 Airflow DAGs in Python on AWS EKS, processing roughly 500 GB of geospatial data a month for more than 10 downstream products. I own it end to end — the Airflow Dockerfile and Helm charts, the Terraform, the Jenkins CI/CD pipeline, the FastAPI services that serve the data, and the monitoring in Datadog and OpenSearch. Two things I'm proud of: coordinating the handover of 141 web scrapers to another business unit, where I validated every output and built the failure alerting that made the handover safe; and co-designing our move from a warehouse-only setup to a proper data lake. Right now I'm leading two migrations — Airflow 2 to 3, and standard S3 to Apache Iceberg (S3 Tables) with dbt and DuckDB. I was formally promoted to mid-level in June 2025.

What I'm interested in: owning a data platform rather than being handed tickets for one. I care most about reliability and clean data modeling — pipelines people trust without double-checking — and I like working close to the domain rather than abstracted from it. My environmental background means I usually understand what the data actually represents, which has been useful in agriculture and would be in climate, energy, geospatial, or logistics. I'm also comfortable being the person who explains the technical work to non-technical stakeholders; the sales years were good for that.

I'm based in Brazil (UTC-3, overlapping both US and European hours), fluent in English (C1 — I lived in Norway on an exchange year and in Australia), and I've worked fully remotely since 2022. I'm looking for remote international roles, ideally as a contractor. Longer term I want to move toward senior data engineering, and I'm interested in teams where the data platform is the product's foundation rather than a side concern.