Python Developer
About the role
This is a web-backend Python role, not a data science one. You will work on the Django application that serves the Auralis product: authentication, workspace and billing management, the reporting API that the React front end calls, and the scheduled jobs that keep customer dashboards fresh.
What the work looks like
Roughly half feature work and half making the existing system faster and easier to reason about. A recent example: our cohort endpoint was doing a query per cohort row and taking eleven seconds on large accounts. Rewriting it as a single aggregate with a materialised intermediate table brought it under 400 milliseconds. That kind of problem shows up regularly.
You will work with two other backend engineers and the data engineering team, who own everything upstream of the warehouse.
What we look for
Two to four years of Python in production, ideally with Django or FastAPI. Real SQL ability matters more than framework familiarity here — you should be comfortable reading a query plan and knowing why an index is not being used. We will happily teach you Django if you know Flask or FastAPI well.
Responsibilities
- Build and maintain Django views, serialisers and background tasks
- Write and optimise the SQL behind the reporting API
- Keep the scheduled refresh jobs reliable and observable
- Add tests to legacy areas as you touch them
- Review pull requests from across the backend team
Requirements
- 2-4 years writing Python in production
- Confident SQL, including joins, window functions and query plans
- Experience with Django, FastAPI or Flask
- Familiar with Postgres and at least one caching layer
- Comfortable with Git-based review workflow
Skills
Benefits
- Four-day office week with Fridays remote
- Health insurance for you and immediate family
- Small team, direct ownership of what you build
- Two paid conference days a year
Auralis Analytics
Auralis builds the analytics layer for consumer subscription businesses: cohort retention, revenue forecasting and churn prediction delivered as a hosted product rather than a consulting engagement.
The stack is deliberately boring. Python, Postgres, Airflow and a columnar warehouse, with a React front end on top. We would rather spend our novelty budget on data modelling than on infrastructure, and we keep the pipeline small enough that one engineer can hold it in their head.
We work from Baner, Pune, four days in office with Fridays remote for everyone.
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