Backend Engineer

6,000+ Customers. 300+ Integrations. Your Code Moves the Data.
At Windsor.ai, we connect data from 300+ sources (Facebook Ads, Google Ads, GA4, HubSpot, Salesforce, TikTok) to 30+ destinations (Looker Studio, BigQuery, Snowflake, and LLMs like ChatGPT and Claude). We're a lean, highly technical remote team serving 6,000+ customers, and we're looking for a Backend Engineer to help scale the platform behind it.
The Role
You'll build and maintain the Python pipelines at the core of our marketing data integration and ELT platform: pulling data from third-party APIs, normalizing it, and delivering it reliably at scale.
Own API integrations end to end: rate limits, pagination, custom authentication, and inconsistent error handling across hundreds of sources.
Ship production-grade code: clean, tested Python with pytest coverage and code review as routine.
Keep pipelines fast and reliable: concurrency, caching, and smart data modeling as volume grows.
Work async with a small, senior team: engineers, product, and support. Basic SQL is expected of everyone.
Stack: Python (Flask, multi-threading), pytest / pytest-xdist, pylint, PostgreSQL, Redis, Linux, Docker, GitLab CI/CD, Taiga.
Who You Are
4+ years of professional programming experience with strong production-grade Python
Solid grasp of OOP, concurrency (threads/async), and data structures
Comfortable in Linux development and production environments
Experience integrating third-party APIs and dealing with their quirks
Independent, async, and comfortable in a fully remote, contractor-style engagement
Bonus: ETL/ELT or data integration experience
marketing/ad-tech APIs
PostgreSQL and Redis in production
Docker and GitLab CI/CD
The Offer
Competitive Pay / Contractor role
Fully remote
Real impact: your code runs in production for 6,000+ customers
Windsor.ai is a global team of data engineers and analysts who strive to make data integration effortless and insights easy to extract to everyone. We help businesses of all sizes connect their marketing and sales data, automate reporting, and measure what drives the greatest impact.

Work arrangement
Yes