Sr Backend Developer (Python / Data Engineering / GCP)

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). • 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).

• 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.

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. Originally posted on Himalayas Backend-Engineer, Data-Engineer, Python-Developer, Software-Engineer, Full-Stack-Developer, Senior-Backend-Python-Developer, Senior-Python-Backend-Developer, Python-Backend-Developer, Python-Backend-Engineer, Senior-Backend-Engineering, Senior-Backend-Development