Sr Backend Developer

Backend Developer (Python / Data Engineering / GCP)

Location:
Remote — LATAM preferred Rate: $27 hourly Commitment: Full-time, 40 hours per week Schedule: U.
S. Central Time business hours Contract: Long-term contractor Hiring timeline: Within two weeks

About the Role
We’re looking for a Backend Developer with strong expertise in Python, data engineering, and Google Cloud Platform (GCP) to own backend services, data pipelines, and cloud infrastructure. You’ll build and operate systems that transform large volumes of data into fast, reliable information for users. Your primary focus will be backend and data engineering, with occasional frontend work in React, Next.js, and TypeScript to deliver complete features. You should understand how data moves through a production system: Data ingestion → processing → storage → serving → APIs → frontend For selected projects, you’ll own the full delivery lifecycle, from technical planning and implementation to deployment, product analytics, and iteration. What You’ll Own
• Build and maintain Python backend services and production APIs.
• Design, develop, and optimize ETL pipelines for large historical and geographic datasets.
• Write advanced SQL and optimize BigQuery queries and workloads.
• Build and manage scheduled jobs, queues, background processes, and asynchronous workflows.
• Operate GCP infrastructure, including Compute Engine, BigQuery, Cloud Storage, Pub/Sub, monitoring, and load balancing.
• Improve how data is precomputed, packaged, cached, compressed, and served.
• Investigate and resolve issues across source data, pipelines, databases, APIs, infrastructure, and the frontend.
• Improve system performance, reliability, scalability, and observability.
• Make frontend changes in React, Next.js, and TypeScript, using AI coding tools to accelerate delivery.
• Deliver selected features end to end, measure adoption and performance, and iterate after launch. Must-Haves
• Strong professional experience building and operating Python backend systems and APIs in production.
• Experience working with BigQuery, advanced SQL, and large datasets.
• Production experience with GCP, particularly Compute Engine, Cloud Storage, and Pub/Sub.
• Experience building ETL pipelines, background jobs, and asynchronous processing workflows.
• Strong skills in data architecture, system design, performance optimization, and debugging.
• Working knowledge of React and JavaScript or TypeScript, with the ability to contribute to an existing frontend codebase.
• Daily use of AI coding tools such as Claude, Cursor, or GitHub Copilot.
• Strong English communication skills for daily standups and one-on-one conversations with leadership.
• Proficiency with Git and modern development workflows.
• Availability to work 40 hours per week during U.
S. Central Time business hours. Nice-to-Haves
• Experience with PostHog or similar product analytics tools.
• Experience working with geographic or time-series data.
• Experience with caching strategies and data packaging for high-traffic applications. Who You Are You’re a hands-on engineer who takes ownership of systems in production. You’re comfortable writing code, investigating bugs, deploying solutions, and resolving issues across the stack. You use AI coding tools regularly to understand unfamiliar codebases, write tests, refactor systems, and implement features. You can evaluate their output and take responsibility for the quality of the code you ship. You don’t need to be a frontend specialist, but you should be comfortable making the changes needed to deliver a complete, usable feature. You care about what happens after launch: whether users adopt a feature, how reliably it performs, and what needs to improve. You communicate proactively, raise risks early, and recommend practical solutions. Who This Role Is Best Suited For Your strongest experience should be in backend development, data engineering, and GCP, with a track record of connecting these disciplines in production. This role is unlikely to be a fit if your experience is primarily:
• Data engineering without building APIs or backend services.
• CRUD-focused backend development with limited experience processing large datasets.
• Frontend development with limited backend and cloud experience. How We Work You’ll collaborate closely with leadership and the development team through daily standups, brief daily one-on-ones, and ongoing communication. We prefer candidates based in LATAM, ideally in UTC-5 or UTC-6 time zones. Candidates in other locations may be considered if they can consistently work U.
S. Central Time business hours.