Data-oriented developer specialized in the full operational data lifecycle: extraction from ERP systems, transformation, modeling, automation, and decision-oriented delivery. Pragmatic approach focused on business usage, reliability, and long-term maintainability.
No academic data science positioning and no experimental machine learning focus. Core work centers on robust pipelines, explicit data models, and BI tools usable by non-technical stakeholders.
- Data extraction and integration
- ETL pipeline design and maintenance
- Relational and analytical data modeling
- Python automation
- Business KPI delivery
- Technical and functional documentation
- Python (automation scripts, data processing, export generation)
- PostgreSQL
- Talend (ETL)
- Metabase (BI, dashboards, access governance)
- Debian (server environment)
- TeamCity (CI/CD)
- Git
- LDAP (role and access structuring for BI)
- Strict naming conventions and data structuring
- Extraction traceability
- Clear separation between business logic and technical logic
- Systematic documentation for handover and audit
- Preference for simple, robust solutions over complex ones
- School 42 — Data / Development specialization
This repository mainly contains:
- Python utility scripts
- Internal data management tools
- Extraction templates and standards
- Usage-driven experiments, not demonstrative projects
- Email: acheldrinker@gmail.com
- LinkedIn: https://linkedin.com/in/hugomartineu