Sr Backend Developer (Python / Data Engineering / GCP)

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.