Staff Software Engineer, Python

Northbeam is building the world's most advanced marketing intelligence platform, providing top eCommerce brands a unified view of their business data through powerful attribution modeling and customizable dashboards. Our technology helps customers accurately track ad spend, understand the full customer journey, and drive profitable growth. Machine learning has been at the heart of Northbeam since day one: our full suite of measurement, spanning multi-touch attribution, MMM+, and incrementality, is built on it, along with laser-accurate first-party data. Now we're taking that foundation further, using AI to help brands operationalize their data and turn Northbeam insights into automated decisions.

We're experiencing rapid growth, have strong product-market fit, and are looking for the right people to help us scale. This is a rare chance to make a meaningful impact at a fast-moving, high-growth company. At Northbeam, you'll join a team of driven, collaborative, and talented individuals who value personal growth and excellence. We'd love for you to be part of our journey.

We're a remote-friendly company with physical offices in San Francisco and Los Angeles.

Northbeam is fundamentally a data product - the whole company. We don’t sell shoes, ads, or games. We sell data: quality integrations with a variety of platforms, fresh and reliable data pulls, robust data ingest APIs, correct aggregations, and algorithmic insights on top of that data, all packaged up in a user-facing application.

What this means for you is that high-quality, robust data integration is at the core of what we do, and your work will have a direct connection to the company’s success.

We're looking for a Staff-level Software Engineer who leans backend and can take product problems from ambiguity through architecture to production. You'll spend roughly 70% of your time on backend and distributed systems work and 20–30% on frontend, giving you the ability to own capabilities across the stack and to make architectural calls that hold up on both sides of it.

You'll take new products from early traction to meaningful scale, and set the technical direction that gets them there. That includes architecting our new incrementality offering into a scalable experimentation platform, defining our approach to near real-time data infrastructure, and establishing how AI shows up in our marketing users' workflows. You'll partner closely with data scientists, product managers, and designers, and your influence on what gets built will be as real as your influence on how.

• Architect our new incrementality product into a reliable, repeatable experimentation platform, and own the technical decisions that determine whether it scales.
• Set the direction for near-real-time ingestion and processing as we move beyond batch workflows.
• Define the patterns for AI-powered workflows that help marketers evaluate performance and act on insights — the first version and the framework that follows it.
• Lead work on connection-state systems and the partner ecosystem across data ingestion and exports.
• Shape technical approach in adjacent product areas such as role-based access control (RBAC).
• Multiply the team: design review, mentorship, and raising the standard for what ships.

• 8+ years designing and building distributed backend systems, microservices, APIs, and/or data processing systems in Python.
• Deep experience owning system architecture, including the tradeoffs that only surface at scale.
• A track record of partnering with product managers, designers, and data scientists to shape what gets built, not only how.
• Startup experience, or experience in an environment demanding breadth, sound judgment, and strong problem-solving under ambiguity.
• Demonstrated ability to turn ambiguous product needs into sound technical architecture and production-ready solutions — repeatedly, across different problem spaces.
• Fluency navigating complex datasets and interconnected tables to investigate issues, trace dependencies, and find the right path forward.
• Working frontend experience with React and TypeScript; deep frontend specialization is NOT required.
• Strong coding fundamentals, with AI used as an accelerator rather than a substitute for core capabilities.
• A generalist mindset and willingness to work across backend, frontend, pipelines, and infrastructure when the product requires it.
• Experience mentoring engineers and improving how a team operates.

• Most of your experience is in data-intensive backend engineering, but you've also shipped frontend work.
• You've been the person a team turns to when the architecture question doesn't have an obvious answer.

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