Senior Software Engineer, Data Systems (Python)

About the Role

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.

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 are looking for a Senior Software Engineer with experience in data integration, API-based ETL pipelines, and cloud-native architecture. 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.

Your Impact

This is a startup. The one thing that’s constant is change. To start with, 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.

You will work with great people who have done this many times before. You will teach them some new tricks, and maybe learn some old ones.

If this sounds like your kind of chaos, we’d love to hear from you.

What You Bring

• 5+ years of experience in data engineering, software engineering, or integration engineering, with a focus on ETL, APIs, and data pipeline orchestration.
• Strong proficiency in Python
• Experience with API-based ETL, handling REST, GraphQL, Webhooks
• Experience implementing authentication flows
• Proficiency in SQL and BigQuery
• Experience with orchestration frameworks (e.g., Airflow) to manage and monitor complex data workflows.
• Familiarity with containerization (Docker, Kubernetes) to deploy and scale workloads.
• Ability to drive rapid development while ensuring maintainability, balancing short-term delivery needs with long-term platform stability.

Bonus

• Detailed understanding of authentication mechanisms (OAuth 2.0, API keys, secrets management) and secure multi-tenant architectures.
• Experience working with ERP systems, CRMs, CDPs, or complex other enterprise data tools and their APIs.
• Exposure to event-driven architectures and real-time data processing tools
• Knowledge of data governance, compliance (GDPR, SOC2), and security best practices for handling sensitive data.
• Experience working in a multi-tenant SaaS or large-scale data-intensive environment.