Live opening · Posted 3 days ago

Backend Developer — Python / Data Engineering / GCP

Reventure App · United States (Remote)
Linkedin Yes
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At a glance

The key details from the original listing.

Posted 3 days ago
CompanyReventure App
LocationUnited States (Remote)
Work modeYes
SourceLinkedin
Listed3 days ago

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About the role

Description supplied by the original job listing.

Location: Hybrid - Nashville TN or Atlanta GA Metro Area
Type: Full-time, 40 hours/week in Central Time
Hiring Timeline: We expect to hire within the next 2 weeks
About Reventure App
Reventure App is the #1 source for housing market data for homebuyers and real estate investors, with more than 2 million users across the U.S.
We’ve built one of the industry’s most accurate housing forecasting systems, with historical testing showing our forecasts are approximately 4x more accurate than Zillow’s. Our feature set is continually expanding across forecasts, valuations, interactive maps, investor analytics, property tools, and AI-driven features.
We also have a massive built-in marketing funnel, with more than 1 million followers across our social media channels. That allows us to launch new features to a large audience, measure how users respond, and iterate quickly.
We’re profitable, growing, and looking for a hands-on, product-minded engineer who wants meaningful ownership of the technology and features behind that growth.
The Role
This is primarily a backend and data engineering role, but we are not looking for someone who simply completes tickets.
We want a developer who thinks like a product owner.
You should enjoy taking a feature from idea to production, taking accountability for whether it actually works for users, and then using real product data to improve it. You should also have some DevOps experience, and understand how to keep an app stable and fix issues that come up.
Your involvement in a new feature might look like:
Product idea → architecture → database/data pipeline → API → front-end implementation → launch → PostHog analysis → iteration
You’ll work directly with the CEO and development team to turn product ideas into working features quickly.
What You’ll Own
Build and maintain our Python backend systems
Design and improve our data architecture
Build and maintain APIs powering our web and mobile applications
Own new product features from technical planning through production
Maintain and improve ETL pipelines processing housing, economic, and geographic data
Write and optimize advanced SQL
Manage asynchronous processes, scheduled tasks, queues, and background jobs
Maintain and improve our Google Cloud Platform infrastructure
Work with services including Compute Engine, Cloud Storage, Pub/Sub, load balancing, and monitoring
Debug issues across data sources, backend systems, APIs, and the user-facing application
Improve system performance, reliability, scalability, and monitoring
Make front-end changes when needed, particularly using modern AI development tools
Help identify architectural weaknesses and propose practical solutions
Think Like a Product Owner
Shipping the code is not the finish line.
We want someone who wants to know:
Are users actually using the feature?
Where are they dropping off?
Are they clicking the actions we expected?
Is the feature improving engagement or conversion?
What should we change next?
Experience with PostHog, Amplitude, or a similar product analytics platform is strongly preferred.
You should be comfortable defining events and funnels, analyzing user behavior, supporting A/B tests, identifying friction points, and using data to recommend product changes.
What We’re Looking For
Strong professional experience with:
Python
Backend development
API design and architecture
ETL and data pipelines
Advanced SQL
Large datasets
Asynchronous and background processing
Google Cloud Platform
Production infrastructure
Data architecture and system design
Git and modern development workflows
Debugging complex production systems
You should also have enough front-end experience to work effectively in an existing application, ideally with:
React
JavaScript / TypeScript
API integration
Front-end debugging
Building or modifying user-facing features
You do not need to be a front-end specialist. Backend and data engineering should be your strongest skill set.
But you should be comfortable using your own coding ability and AI tools to work across the stack when needed.
AI-Native Development
We actively encourage the use of modern AI development tools such as Claude, Cursor, GitHub Copilot, and similar platforms.
We’re interested in developers who use AI as a force multiplier to:
Understand unfamiliar code faster
Build features more quickly
Work outside their primary specialization when necessary
Debug issues
Write and review tests
Refactor code
Analyze architecture
Automate repetitive engineering work
We care about quality and output, not whether every line of code was typed manually.
Working Style
This is a hands-on engineering role.
You will be expected to write code, investigate bugs, build features, troubleshoot production issues, and deploy solutions yourself.
Our development cadence includes:
40 hours per week
Working primarily during Central Time business hours
Daily development standups
Brief, regular 1-on-1 check-ins with the CEO
Direct communication about priorities, blockers, architecture, and product decisions
Close collaboration with developers and QA
You will have substantial ownership and direct access to the person making product decisions, allowing good ideas and technical improvements to move quickly.
We value proactive communication. If something is blocked, behind schedule, or architecturally risky, we want to know early — along with your recommended solution.
Who Will Succeed Here
You’ll likely do well if you:
Think like a product owner as much as an engineer
Want ownership of features rather than just assigned tickets
Care whether users actually use what you build
Use data to evaluate your work
Can turn loosely defined ideas into workable technical solutions
Investigate problems independently
Think about architecture and long-term maintainability
Can move between backend, data, APIs, infrastructure, and occasional front-end work
Use AI aggressively and intelligently to increase your productivity
Communicate proactively
Enjoy working in a fast-moving product environment
Location
This is a hybrid position. We are specifically looking for candidates located in the Nashville, TN or Atlanta, GA metro areas who can work a consistent 40-hour week, primarily aligned with Central Time.
The CEO regularly splits time between Nashville and Atlanta, so this role is best suited for someone comfortable with regular in-person collaboration at our local office in their city when the CEO is there. This may include brainstorming, reviewing priorities, working through projects together, and helping move initiatives forward.
Candidates should expect to work in person 1–2 days per week at our local Nashville or Atlanta office, depending on the CEO’s schedule and location that week.
Hiring Process
We are moving quickly and expect to make a hire within the next two weeks.
When applying, please briefly answer the following:
1) Describe the most complex backend or data system you have personally built or owned. What was the architecture, scale, and your specific responsibility?
2) Rate your Python skills from 1–5, with 5 being expert-level. Briefly describe the most advanced production work you have personally done in Python.
3) Rate your Google Cloud Platform skills from 1–5, with 5 being expert-level. Which GCP services have you used in production, and what did you personally build or manage?
4) Suppose you were given 20–30 years of population, housing, income, and migration data for roughly 30,000 U.S. ZIP codes and asked to forecast population five years forward. How would you approach it?
5) How would you approach building and validating a home-price forecast for every ZIP code in the U.S.? What variables would you consider, and how would you test forecast accuracy?
6) Describe a large ETL or data pipeline you personally built or maintained. What tools did you use, how much data did it handle, and what was the hardest problem you solved?

Work arrangement
Yes

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