Senior Django developer a mortgage and protection advice platform (full-time, remote, UK/EU)
Buget: -
HOURLY / FULL_TIME
⭐ 5.00 (29)
United Kingdom
postgresql, django-framework, python, celery, data-migration
Calificări preferate
- Locație: Europe, United Kingdom
- Experiență: Expert
We build the platform a group of UK mortgage and protection advice firms runs on. One client record, one case pipeline, one audit trail. It is in production and used daily by advisers.
The work
New API endpoints, models and migrations for a live multi-tenant Django application
Integrations with third-party services: REST, SOAP, browser-driven
Celery background jobs: credit searches, sourcing runs, PDF generation
Data migrations from other systems into ours
Production hardening: audit trails, permissions, performance
The codebase
Python 3.13, Django, Django REST Framework, Celery, PostgreSQL. Monolith, about 50k lines, typed throughout, strict ruff, tests beside the code. Pull requests with review, Kubernetes on AWS.
You
5+ years of Python, 3+ years of Django and Django REST Framework in production
PostgreSQL: schema design, migrations, query performance
Celery or a similar task queue
Experience integrating third-party APIs (REST, SOAP)
Tests as a normal part of the work
UK or EU based. NDA and IP assignment under English law before repository access.
Bonus: React and TypeScript, AWS, fintech or lending experience.
Terms
Hourly, 35–40 hours a week. Paid three-week trial on a scoped task, then a long-term contract if it works for both sides. Four hours overlap with UK time. Small team, decisions the same day, one Slack channel.
To apply
Start your proposal with "Hub" and answer the questions below. Short answers are fine.
Proposals without answers will not be read.
1. We keep the full XML request and response of every credit bureau call in a PostgreSQL text column. A colleague proposes converting them to JSONField with a GIN index so we can search them. What do you tell them?
2. Our credit search runs as a Celery task. A colleague suggests wrapping the whole task in transaction.atomic so any failure rolls back cleanly. Good idea?
3. A client asks a regulated advice firm to erase their data. Hard delete, soft delete, or anonymise? Pick one and say what it breaks.
4. The last Django or PostgreSQL upgrade that broke something for you: which versions, what exactly broke, how you found it, what you changed.
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