🧩 What This Covers#
I design workflows that transform raw, inconsistent, or multi-source data into a clean and usable state. This includes logic-heavy shaping, business rule application, and preparing data for modeling, reporting, or further automation.
🛠Common Scenarios#
- You’re spending too much time reshaping or cleaning data manually
- Your transformation logic is spread across disconnected scripts or spreadsheets
- You need to apply consistent business logic across datasets
- Your data sources are messy, nested, or require normalization
- You want traceable, versioned transformation pipelines
📌 What I Focus On#
- Applying structured, layered transformations (e.g., raw → staged → clean)
- Making business logic transparent and testable
- Avoiding unnecessary complexity - simple where possible, robust where needed
- Designing workflows to be modular, reusable, and easy to maintain
- Aligning transformations with upstream and downstream needs
🚀 Outcomes You Can Expect#
- Clean, consistent data that’s ready for reporting or modeling
- Fewer manual data prep steps and one-off scripts
- Clear logic that’s easy to validate and troubleshoot
- Transformation workflows that scale with your data volume and structure