- Страна
- США
- Зарплата
- 176 000 $ – 282 000 $
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Software Engineer – Backend, Pricing
Отличное предложение от известной компании с прозрачным диапазоном зарплаты, бонусами и RSU. Интересные задачи на стыке Backend и Data Science в технологически продвинутом стеке.
Сложность вакансии
Высокая сложность обусловлена требованиями к глубоким знаниям распределенных систем, SQL оптимизации и опыту работы с Go/Python от 5 лет. Позиция Senior уровня предполагает лидерство в технических проектах и тесное взаимодействие с Data Science командами.
Анализ зарплаты
Предложенная вилка $176k–$282k полностью соответствует и даже несколько превышает рыночные стандарты для Senior Backend инженеров в Сиэтле. Верхняя граница диапазона характерна для топовых технологических компаний (Big Tech).
Сопроводительное письмо
I am writing to express my strong interest in the Senior Backend Software Engineer position on the Pricing team at Opendoor. With over 5 years of experience in backend development and a deep proficiency in building scalable microservices using Go and Python, I am excited about the opportunity to contribute to the engine that powers Opendoor’s core business. My background in designing high-performance SQL systems and managing complex data models aligns perfectly with your team's mission to deliver fast and accurate pricing decisions.
In my previous roles, I have successfully led technical projects from design to deployment, focusing on system reliability and scalability. I am particularly drawn to Opendoor's innovative approach to real estate and the technical challenge of productionizing complex pricing models. I am confident that my experience with distributed systems and my ability to collaborate effectively with data science and product teams will allow me to make a significant impact on your pricing platform.
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Описание вакансии
Software Engineer – Backend, Pricing (Senior level or higher)
Seattle, WA
About the Team
The Pricing team is the engine behind Opendoor’s ability to price homes with speed, scale, and confidence. We build the core platform that turns data, models, and business logic into the prices that power our entire business.
We own mission-critical services and data infrastructure that support pricing decisions and automation. Our systems must be fast, accurate, and resilient—because small improvements can translate into major business impact.
As a software engineer on the team, you’ll collaborate with data scientists, machine learning engineers, product managers, and partner engineering and operations teams to turn ideas into resilient, production-ready systems. You’ll see your work move from design to deployment quickly and have meaningful ownership over how our pricing platform evolves and how we shape the future of real estate.
What You’ll Do
- Own the design, implementation, and evolution of core pricing services
- Design data models and write high-performance SQL over large PostgreSQL datasets
- Architect and improve APIs and integrations with Opendoor’s core marketplace platform
- Lead technical design reviews and set best practices for code quality, testing, and observability
- Partner with data science to productionize pricing models and build robust model-serving pipelines
- Drive reliability, latency, and scalability improvements across pricing systems
- Mentor other engineers and help grow the technical capabilities of the team
- Collaborate with product and cross-functional partners to define and deliver roadmap projects end to end
What You’ll Need
- 5+ years of professional backend software engineering experience
- Significant experience building and operating production systems in Go or Python
- Deep proficiency with SQL and relational databases (PostgreSQL preferred)
- Strong track record designing, building, and evolving APIs in a microservices environment
- Experience with distributed systems concepts (scalability, consistency, resiliency, monitoring)
- Experience leading technical projects from design through rollout and support
- Ability to communicate complex technical decisions clearly to both technical and non-technical stakeholders
Nice to Have
- Experience with Kafka or similar event-streaming technologies
- Experience using AI-assisted development tools (e.g. Claude Code, Cursor AI, Github Copilot)
- Experience with BPMN or other workflow engines and long-running business processes
- Experience with Redis or other caching / storage optimization technologies
- Experience with gRPC and service-to-service communication patterns at scale
- Prior experience in pricing, marketplaces, or other data-intensive domains
Compensation
The base pay range for this position is $176,000-$282,000 annually, plus RSUs and bonuses. Pay within this range varies by work location and may also depend on your qualifications, job-related knowledge, skills, and experience. We also offer a comprehensive package of benefits including unlimited PTO, medical/dental/vision insurance, life insurance, and 401(k) to eligible employees.
#LI-RO
At Opendoor our mission is to tilt the world in favor of homeowners and those who aim to become one. Homeownership matters. It's how people build wealth, stability, and community. It's how families put down roots, how neighborhoods strengthen, how the future gets built. We're building the modern system of homeownership giving people the freedom to buy and sell on their own terms. We’ve built an end-to-end online experience that has already helped thousands of people and we’re just getting started.
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Навыки
- Go
- Python
- SQL
- PostgreSQL
- Microservices
- Distributed Systems
- Kafka
- Redis
- gRPC
- BPMN
Возможные вопросы на собеседовании
Проверка опыта работы с высоконагруженными БД, что критично для систем ценообразования.
Расскажите о самом сложном случае оптимизации SQL-запроса в PostgreSQL на больших объемах данных. Каких результатов удалось достичь?
Оценка навыков проектирования архитектуры в микросервисной среде.
Как бы вы спроектировали систему ценообразования, которая должна обеспечивать низкую задержку (latency) при высокой консистентности данных?
Проверка умения работать на стыке инженерии и анализа данных.
Опишите ваш опыт вывода ML-моделей в продакшн (productionizing). С какими основными трудностями вы сталкивались при построении пайплайнов?
Оценка понимания принципов отказоустойчивости.
Какие стратегии обеспечения отказоустойчивости (resiliency) вы применяли в распределенных системах при интеграции со сторонними сервисами?
Проверка навыков менторства и лидерства.
Приведите пример, когда вам приходилось принимать сложное архитектурное решение, с которым не все были согласны. Как вы аргументировали свою позицию?
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- Страна
- США
- Зарплата
- 176 000 $ – 282 000 $