Software Engineer, Data Systems (Python)

Northbeam is fundamentally a data product - the whole company. We don’t sell shoes, or 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. 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.

You will work with a small engineering team to create a platform that consolidates third-party data from a wide range of sources, including advertising platforms, e-commerce systems, customer data warehouses, ERP, POS, and CRM systems. You will need to think about concerns like scalability, multi-tenancy, batch vs streaming trade-offs, data validation, API design, and more.

You will work with experienced engineers who are eager to share their knowledge and experience, and to learn alongside you. Curiosity, willingness to do the hard thing, attention to developer ergonomics, and an enjoyment of a startup pace of development will be the key to success in this role. This is a startup with constant change, so you can expect to design and implement scalable, high-performance data pipelines to ingest and transform data from a variety of sources, ensuring reliability, observability, and maintainability. Build and maintain APIs that enable flexible, secure, and tenant-aware data integrations with external systems. Work with event-driven and batch processing architectures, ensuring data freshness and consistency at scale. Drive clean API design and integration patterns that support both real-time and batch ingestion while handling diverse authentication mechanisms (OAuth, API keys, etc.). Implement observability, monitoring, and alerting to track data freshness, failures, and performance issues, ensuring transparency and reliability. Optimize data flows and transformations, balancing cost, efficiency, and rapid development cycles in a cloud-native environment. Collaborate with data engineering, infrastructure, and product teams to create an integration platform that is flexible, extensible, and easy to onboard new sources.