Victor de Moraes
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Data Automation Engine

Data Automation Engine is a small, reproducible Python CLI for validating operational CSV records and producing clean output, rejected-record details, a summary, and a run log without exposing private client data.

Overview

The project models a practical data workflow: receive input files, validate business rules, normalize records, generate reports, export logs, and produce an actionable summary for operational teams.

Tech Stack

  • Python
  • CSV and standard-library data processing
  • Automated tests
  • GitHub Actions

Architecture

  • CLI/API entry point for operational jobs.
  • CSV ingestion and schema validation.
  • Deterministic rules for IDs, names, and positive amounts.
  • Clean output plus rejected-record details.
  • Summary and run log for support and reprocessing.

Production Practices

  • CI/CD pipeline with GitHub Actions.
  • Reproducible local CLI execution.
  • Tests for valid, invalid, and malformed input.
  • Logs and error files for traceability.
  • Clear separation between input, processing, output, and operational reporting.

Operational Notes

The repository is designed as a public replacement for confidential automation work: it demonstrates data validation, workflow automation, operational reporting, and production-minded delivery practices.