Python Engineer
About the Company:
Northbeam builds a marketing intelligence platform that helps leading eCommerce brands understand their performance through unified business data, attribution modeling, and customizable dashboards. Its technology enables customers to track advertising spend, understand the customer journey, and make better decisions to improve profitability. Machine learning is central to Northbeam's measurement products, including multi-touch attribution, MMM+, and incrementality. The company is now expanding its use of AI to help marketing teams turn insights into automated decisions. Northbeam is growing rapidly and operates as a remote-friendly company with offices in San Francisco and Los Angeles.
About the Role:
Northbeam is looking for a mid-level Software Engineer with a strong backend focus and an interest in building complete product features across the stack. Approximately 70% of the role will involve backend development, while 20–30% will focus on frontend work. You will help develop new products and expand existing capabilities, working on backend services, data processing systems, and the frontend components needed to deliver complete user experiences. Projects may include expanding the incrementality product into a scalable experimentation platform, building near-real-time data infrastructure, and introducing AI-powered workflows for marketing teams. You'll collaborate closely with data scientists, Product Managers, designers, and senior engineers. This role suits an engineer who can take defined requirements through implementation and production, adapt to changing priorities, and contribute across backend systems, frontend development, data pipelines, and infrastructure as needed.
Key Responsibilities:
- Contribute to the development of Northbeam's incrementality product as it evolves into a reliable, repeatable experimentation platform.
- Build and maintain backend services, APIs, and data processing systems using Python.
- Help develop near-real-time data ingestion and processing capabilities as the platform expands beyond batch-based workflows.
- Build AI-powered workflows that help marketers evaluate performance and act on insights.
- Improve connection-state systems and expand partner integrations across data ingestion and data exports.
- Contribute to other product areas, including role-based access control (RBAC).
- Develop frontend components when needed to deliver complete product features and user experiences.
- Translate product requirements into working, production-ready code.
- Investigate issues involving unfamiliar datasets and interconnected tables, trace dependencies, and work toward effective solutions.
- Collaborate with Product Managers, designers, data scientists, and senior engineers throughout the development process.
- Take ownership of implementation through production while considering reliability, maintainability, and the broader product architecture.
- Adapt to changing product priorities and contribute across different technical areas when needed.
- Use AI development tools to improve productivity while applying sound engineering judgment and independent problem-solving skills.
Required Qualifications:
- At least 3 years of experience developing backend services, APIs, and/or data processing systems using Python.
- Exposure to distributed systems or microservices, with an interest in understanding how larger architectures work together.
- Experience collaborating with Product Managers, designers, and data scientists.
- Experience taking ownership of implementations through production.
- Ability to translate defined product requirements into reliable, production-ready code.
- Ability to investigate unfamiliar datasets, understand relationships between interconnected tables, and trace dependencies, with support when needed.
- Working knowledge of frontend technologies such as React and TypeScript; deep frontend specialization is not required.
- Strong programming fundamentals, practical problem-solving skills, and the ability to use AI as a development aid rather than a substitute for core engineering knowledge.
- Comfort working in a fast-moving or early-stage environment where priorities can change and engineers contribute wherever the product needs support.
- A generalist mindset and willingness to work across backend development, frontend features, data pipelines, and infrastructure. Preferred Experience and Working Style
- A background in data-intensive backend engineering combined with experience delivering frontend features.
- An interest in building scalable data systems, experimentation capabilities, and AI-powered product experiences.
- The ability to work independently on defined tasks while collaborating with senior engineers on more complex architectural decisions. Work Arrangement
- Remote-friendly work environment.
- Physical offices in San Francisco and Los Angeles.
- Collaboration with cross-functional product and engineering teams.
Compensation and Benefits:
- Base salary range: $140,000–$155,000 USD.
- Equity package.
- Medical, dental, and vision coverage.
- 401(k) plan.
- Flexible paid time off.
- 12 company-paid holidays.
- 12 weeks of paid parental leave.
- $500 work-from-home stipend. Actual compensation may vary based on experience, skills, and location.
Interview Process:
The interview process typically includes five to seven interviews and requires approximately five to eight hours of candidate time. Stages generally include:
- A 30-minute interview with a Northbeam recruiter.
- A video interview with the hiring manager.
- A role-specific video interview.
- Video or onsite interviews with several team members.
- A final video interview with the CEO/co-founder.
The exact process may vary depending on the role.
Equal Employment Opportunity
Northbeam does not discriminate on the basis of any protected group status under applicable law. The company may ask candidates to complete a voluntary self-identification survey for government reporting and equal employment opportunity purposes. Participation is voluntary, and responses are maintained confidentially and are not considered in hiring decisions.