Data Engineer focused on building production-ready ETL pipelines, analytics warehouses, and reliable data systems.
Core technologies I use to build ETL pipelines, validate schemas, transform source data, load analytics models, and manage reproducible data engineering workflows.
A production-style case study showing raw-to-processed transformations, analytics loading, schema validation, and reproducible PostgreSQL pipeline execution.
Built an end-to-end data engineering case study around the Brazilian Olist e-commerce dataset, evolving it into a production-grade ETL and analytics pipeline with clean transformation stages, warehouse loading, reset logic, and full pipeline orchestration.
Selected work showing ETL development, warehouse loading, orchestration readiness, and practical analytics-focused data engineering.
Developed a modular end-to-end ETL pipeline that transforms raw commerce data into validated processed datasets and loads analytics-ready models into PostgreSQL.
Designed the pipeline with orchestration in mind, focusing on maintainability, execution order, and operational reliability rather than one-off manual scripts.
Designed an analytics-oriented schema that moves beyond raw source files into structured dimensions and fact tables for reporting, analysis, and future optimization.
A concise view of the business challenge, engineering approach, and pipeline architecture behind the project.
PayFlow needed a stronger data foundation for e-commerce expansion. Raw source tables were fragmented across customers, sellers, orders, items, and payments, making direct analytics and operational reporting inconsistent, difficult to maintain, and harder to scale.
Built a production-grade ETL workflow that cleans raw source tables, transforms them into processed datasets, and loads validated dimensions and fact tables into a PostgreSQL analytics schema for downstream reporting and analysis.
The project emphasizes raw → processed → analytics architecture, schema validation, modular loaders, reproducible reset logic, structured logging, and maintainable pipeline orchestration aligned with real data engineering workflows.
View RepoAccess my CV for a detailed overview of my skills and industry experience.
You can download my latest CV as a PDF for offline review or sharing with your team.
Download CVInterested in data engineering, ETL, database design, or analytics-focused opportunities. Reach out through any of the channels below.
I’m open to graduate roles, junior data engineering opportunities, portfolio reviews, and conversations around building reliable data workflows.