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The role involves end-to-end ownership of backend services, data engineering pipelines, and API development using Python and GCP. Additionally, the engineer will utilize AI tools to manage frontend adjustments and monitor product performance.
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.
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