Backend Developer Python / Data Engineering / GCP Latino Legends is partnering with a growing U.S. housing market data company to find a hands-on Backend Developer who can take ownership of backend systems, data pipelines, and GCP infrastructure while contributing to features across the full product.
THE DETAILS
- Compensation: $37–$42 USD/hour
- Location: Remote from Latin America
- Schedule: Full-time, 40 hours/week aligned with US Central Time
- Type: Long-term international independent contractor
- Hiring timeline: ASAP
ABOUT THE ROLE
- This is primarily a backend and data engineering role, with strong ownership across the full product lifecycle.
- You'll work with Python services, APIs, ETL pipelines, BigQuery, production jobs, and GCP infrastructure that processes large-scale housing and economic datasets.
- You'll also contribute to frontend features using React, Next.js, and TypeScript, leveraging AI coding tools to take projects from technical planning through launch and iteration.
- The ideal candidate is not a ticket-closer. You should be comfortable owning a feature end-to-end and thinking beyond whether the code works — including performance, reliability, user adoption, and what should improve after launch.
WHAT YOU'LL DO
- Build and maintain Python backend services and APIs
- Design and optimize ETL and large-scale data processing pipelines
- Work extensively with BigQuery and advanced SQL
- Manage scheduled jobs, queues, background processes, and asynchronous workflows
- Work with GCP infrastructure including Compute Engine, Cloud Storage, Pub/Sub, monitoring, and load balancing
- Optimize how data is precomputed, packaged, cached, compressed, and served
- Debug issues across data sources, pipelines, databases, APIs, infrastructure, and the frontend
- Contribute to React/Next.js/TypeScript features using AI coding tools
- Own selected features from architecture and data pipeline through API, frontend, deployment, analytics, and iteration
- Monitor performance, reliability, scalability, and product usage after launch
MUST-HAVES
- Strong professional experience with Python backend development and production APIs
- Advanced SQL and hands-on BigQuery experience with large datasets
- Production experience with Google Cloud Platform (GCP)
- Strong experience building ETL/data pipelines
- Experience with asynchronous processing and background jobs
- Strong understanding of data architecture, system design, performance optimization, and debugging
- Enough React, JavaScript, or TypeScript experience to work productively within an existing frontend codebase
- Daily experience using AI coding tools such as Claude, Cursor, or GitHub Copilot
- Strong English communication skills for daily standups and 1:1s with the CEO
- Experience with Git and modern development workflows
NICE-TO-HAVES
- Experience with PostHog or other product analytics platforms
- Experience working with geographic or time-series data
- Experience with caching and data packaging for high-traffic applications
THIS ROLE IS NOT A FIT IF...
- Your experience is primarily data engineering without building APIs or backend services
- Your backend experience is mostly CRUD applications without large-scale data
- Frontend development is your strongest skill set
- Backend, data engineering, and GCP are not clearly your strongest areas
AI-NATIVE DEVELOPMENT
- The team actively uses AI coding tools such as Claude, Cursor, and GitHub Copilot.
- You should be comfortable using AI to understand unfamiliar code, troubleshoot bugs, write tests, refactor systems, and build or modify frontend features independently.
WORKING STYLE
- Hands-on and highly technical — you'll write code, investigate bugs, deploy solutions, and troubleshoot production systems
- Proactive and ownership-driven — identify blockers, risks, and reliability issues early and recommend solutions
- Comfortable working 40 hours/week with consistent availability during Central Time business hours
- Collaborative — you'll work closely with the CEO and development team through daily standups, brief daily 1:1s, and ongoing communication
- Product-minded — you care about whether features are actually used, how they perform, and what should be improved after launch
WHAT MATTERS MOST
- The strongest candidates will bring a combination of: Python backend + APIs + data engineering + GCP
- You should be capable of taking a feature from: Architecture → Data Pipeline → Database → API → Frontend → Launch → Analytics → Iteration
- This is an opportunity for someone who wants real ownership over a growing product and enjoys solving complex backend, data, and infrastructure challenges.