🧩 What This Covers#
I build automation systems that adapt to metadata - allowing workflows to scale across tables, datasets, or reporting assets without duplicating logic. This approach reduces maintenance, improves consistency, and makes change easier to manage.
🛠Common Scenarios#
- You have similar logic repeated across multiple scripts, reports, or pipelines
- Changes in structure or logic require too many manual edits
- You’re building a reporting layer across many datasets or regions
- You need flexible workflows that respond to dynamic input
- You want more maintainable and modular automation
📌 What I Focus On#
- Structuring metadata so it can drive logic, not just describe it
- Building parameterized workflows that adapt to inputs
- Reducing hardcoded values and repeated logic
- Applying consistent structure across data models, transformations, and outputs
- Making it easy to update one place, not many
🚀 Outcomes You Can Expect#
- Scalable automation across similar data structures
- Easier updates, fewer breakages, and faster iteration
- Clearer governance and standardization
- Workflows that evolve without starting from scratch