Choose database engine and make table

## Goal
Decide on the database engine for the project and create the schema tables.
See the full design in [`docs/database-design.md`](docs/database-design.md).

## Options
- **Option 1 — Start on SQLite, switch to PostgreSQL for deployment**
- Dev: SQLite (zero setup, Django default)
- Prod: PostgreSQL (best Django fit, handles the daily batch + concurrent users)
- **Option 2 — Use PostgreSQL from the start (local + prod)**
- Run Postgres locally (e.g. via Docker) so dev and prod match
- Avoids subtle SQLite↔Postgres differences (case sensitivity, etc.)

Both engines are free; MySQL was considered but skipped (Postgres is the Django standard).

## Decision
- [ ] Pick Option 1 or Option 2

## Tasks
- [ ] Configure `DATABASES` in `settings.py`
- [ ] (If Postgres) `pip install psycopg2-binary` + add DB env vars
- [ ] Create models: `USERS`, `FAVOURITE_JOBS`, `SAVED_SEARCHES`, `DEMAND_SNAPSHOTS`, `JOB_POSTINGS`

## References
- Schema + engine comparison: `docs/database-design.md`

Start by reading docs/database-design.md and compare the two database options before changing settings.py. Confirm the engine decision, configure DATABASES and any stated PostgreSQL dependency or environment variables, then create the five listed models. Done means the decision checklist and all listed task checkboxes are complete.

Written by the indexing model from the issue text.