Backend Developer

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.

• 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

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.

• 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

• 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

• 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

• 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 should clearly be your strongest areas.

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.

• 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

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.

Originally posted on Himalayas