Tagline: FastAPI backend and analytics system for poultry operations - enforcing business rules and flock tracking in PostgreSQL.
Problem: Broiler farming requires tracking flock cycles, mortality, feed usage, and expenses. Manual records make it difficult to connect operational performance with financial results and detect health anomalies before losses occur.
Key Engineering Decisions
PostgreSQL database CHECK constraints prevent invalid biological and financial data states at the storage layer.
Raw SQL via asyncpg calculates Feed Conversion Ratio (FCR) and flock analytics using Common Table Expressions and window functions.
Domain modular architecture isolates flock lifecycle, health, and expense logic.
Numbered SQL migrations provide explicit, deterministic schema evolution across deployments.
Case study by Fredrick Nyang'au, Backend Engineer based in Nairobi, Kenya, open to remote roles worldwide. Builds backend systems with Python, FastAPI, PostgreSQL, and M-Pesa Daraja integrations.