Sr Backend Developer (Python / Data Engineering / GCP)
Summary
A hands-on senior engineer owning backend and data engineering (~80%): building Python services/APIs, ETL pipelines, and BigQuery/SQL workloads on GCP for real-estate data spanning 30,000+ ZIP codes, with light frontend work in React/Next.js/TypeScript done via AI coding tools (Claude, Cursor, Copilot). Remote in Mexico with Central Time availability.
The Role:
This is not a pure backend role, nor is it a "ticket-closing" position. It is a hands-on role focused primarily on Backend + Data Engineering (80%), where the engineer owns features end-to-end: from data ingestion, ETL processing, BigQuery, and APIs, all the way to shipping on the frontend (React/Next.js/TypeScript) using AI tools (Claude, Cursor, GitHub Copilot).
Responsibilities:
Backend & APIs: Build and maintain Python backend services, APIs, and asynchronous workflows in production.
Data Engineering & SQL: Design and optimize ETL pipelines, scheduled jobs, and complex BigQuery queries on large historical and real estate datasets (30,000+ ZIP codes).
GCP Infrastructure: Manage Google Cloud Platform services (Compute Engine, BigQuery, Cloud Storage, Pub/Sub, monitoring, and load balancing).
Optimization & Caching: Precompute, package, compress, and cache data to serve high-traffic applications efficiently.
AI-Enabled Full-Stack Development: Make frontend adjustments (React, Next.js, TypeScript) using AI assistants to connect backend APIs to the UI without needing a dedicated frontend developer.
Product Ownership & Analytics: Monitor features in production to evaluate user adoption and performance using product analytics (PostHog).
Requirements:
Python & APIs: Strong professional experience developing production backend systems and APIs in Python.
BigQuery & Advanced SQL: Deep expertise with BigQuery and advanced SQL working with large datasets (historical/geographic data).
Production GCP: Direct experience managing GCP infrastructure (Compute Engine, Cloud Storage, Pub/Sub).
ETL & Async Processing: Experience building ETL pipelines, background jobs, queues, and asynchronous workflows.
Functional Frontend Skills: Enough React / Next.js / TypeScript knowledge to productively work inside an existing frontend codebase.
AI-Native Development: Daily hands-on use of AI coding tools (Claude, Cursor, Copilot) for refactoring, writing tests, and building frontend components.
Communication & Availability: Fluent English for daily 1:1 calls with the CEO and full availability during Central Time hours.
Nice-to-Haves:
Experience with product analytics tools (PostHog, Mixpanel).
Work with geographic (GIS) or time-series data.
Caching and data packaging strategies for high-traffic applications.