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You will own the development and maintenance of Python backend services, APIs, and large-scale ETL data pipelines within a GCP environment. Additionally, you will contribute to frontend features using React and TypeScript while ensuring system reliability and performance.
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.
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