Data systems · Cloud · Analytics

Carlos Eduardo de Souza Data Engineer

I build dependable data foundations and turn complexity into systems people can trust.

01 Source raw signals
02 Shape reliable models
03 Serve useful outcomes

A practice of making data useful.

01 / About

Engineering data with clarity and purpose.

I'm a Data Engineer with a background in Physics Engineering, drawn to the point where rigorous thinking meets practical systems.

Since 2022, I have worked across cloud data environments, beginning with GCP and now focusing on Azure. I am currently deepening that practice through an operations-focused MBA in Data Science and Data Analytics at Poli-USP PRO.

02 / Experience

Hands-on data engineering with measurable impact.

  1. May 2025 — now

    Data Engineer, NTT DATA (AB InBev)

    Supported QA validations and sign-offs across 8 business-critical domains using Python, Pandas, and PySpark on Databricks.

  2. Feb 2025 — May 2025

    Data Engineer, Infosys (Kraft Heinz)

    Contributed to refactoring a 10k+ line Java Azure Function monolith and to batch-write optimizations, reducing the heaviest file runtime from 25 minutes to 1 minute.

  3. Sep 2022 — Jan 2025

    Data Engineer, Infosys (Braskem)

    Participated in migrating a core workload from ADF Mapping Data Flow to Databricks, cutting runtime from up to 6 hours to 1 hour and monthly cost from R$20k+ to around R$500-1,000.

  4. Jul 2021 — Sep 2022

    Data Engineer, Raccoon Digital Marketing

    Helped build a self-service DAG generation model on Airflow/BigQuery that ran about 1,000 DAGs and scaled beyond 3,000 shortly after.

  5. Certifications

    Microsoft Certified: Fabric Data Engineer Associate (DP-700)

    Issued by Microsoft in Oct 2025.

  6. Apr 2023

    Microsoft Certified: Azure Data Fundamentals

    Core cloud and analytics data foundations on Azure.

  7. 2022 — 2023

    Astronomer + Udacity Data Certifications

    Apache Airflow Fundamentals, DAG Authoring for Airflow, and Data Engineering with AWS.

03 / Writing

Notes from the work.

View all

04 / Projects

Things built to learn.

Projects will land here soon.

A considered selection of data systems, experiments, and tools will be documented here as they become ready to share.