Design Rule-Based Data Transformation Service Architecture + ERD

We're building an AI-driven financial data analysis and market prediction platform. We need a backend/data architect to design the architecture and ERD (Entity-Relationship Diagram) for a Transformation Rules Service - one component within the "Silver Zone" of our pipeline (full context in the attached brief).

What we need:

The service must let us define transformation rules dynamically (e.g. a rule like A + B = C, where A, B, C are data fields) without hardcoding them. Each rule's logic should live in a Python method, callable from a Python file. We need your ERD to clearly show:

Where field/attribute definitions (A, B, C) are stored
Where the rule logic/expression itself is stored
Where the Python file/method references for each rule are tracked
The dependency relationships between these entities (not an execution sequence)

New rules should be addable at runtime via API endpoints and triggered dynamically - no code changes needed to add a new rule.

Scope: Only the Transformation Rules Service within the Silver Zone. Excludes: Bronze Zone text cleaning/normalization (separate processor), other service APIs, and Market Impact Prediction (Gold Zone).

Deliverables:

Architecture diagram of the Transformation Rules Service
ERD covering fields/attributes, rules/logic, and Python file/method references, with dependencies mapped
A short write-up explaining how a new rule gets added and executed end-to-end, including API usage

Full detailed brief (with diagram) attached - please review before applying.

Skills required: Software/Data Architecture, Database Design (ERD), Python, System Design, API Design

This is very very small task for professional. Budget is fixed. I need to complete this within 24 hours from project started. requirements also fixed. no change.