Senior Software Engineer (Python/Data & Infrastructure)

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 into a user-facing application.

High-quality, reliable data integration is at the core of what we do, and your work will directly shape the company’s success. But building great data products also means building great infrastructure: scalable systems, resilient pipelines, and reliable platforms that empower everything else.

We are looking for a Senior Software Engineer with experience in data integration, API-based ETL pipelines, and cloud-native architecture, plus a strong interest in infrastructure engineering. You’ll help us not just ship data pipelines, but also design the systems that make them observable, secure, and resilient at scale.

You’ll work with a small engineering team to create a platform that consolidates third-party data from advertising platforms, e-commerce systems, customer data warehouses, ERP, POS, and CRM systems. Along the way, you’ll tackle questions of scalability, multi-tenancy, system reliability, data validation, cost optimization, and developer ergonomics.

Curiosity, willingness to do the hard thing, and an enjoyment of a startup pace of development will be the key to success in this role.

This is a startup. The only constant is change. Early on, you can expect to:

• Design and implement scalable, high-performance data pipelines to ingest and transform data from a variety of sources, with reliability and observability baked in.
  
• Engineer the infrastructure behind those pipelines, including containerized workloads, orchestration, monitoring, and CI/CD that enables the team to move quickly without breaking things.
  
• Build and maintain APIs that enable flexible, secure, and tenant-aware data integrations with external systems.
  
• Balance event-driven and batch processing architectures, ensuring data freshness, correctness, and cost efficiency.
  
• Implement observability, monitoring, and alerting to track system health, failures, and performance issues—covering both data quality and infrastructure reliability.
  
• Contribute to platform resilience by designing for fault tolerance, autoscaling, and graceful failure handling in a multi-tenant cloud environment.
  
• Collaborate across data engineering, infrastructure, and product teams to ensure that the integration platform is flexible, extensible, and easy to onboard new data sources.

You will work with great people who have built systems like this before. You’ll teach them some new tricks—and maybe learn some old ones.

• 5+ years of experience in data engineering, software engineering, or infrastructure-focused engineering, with a focus on ETL, APIs, and cloud-native orchestration.
  
• Strong proficiency in Python.
  
• Experience with API-based ETL, handling REST, GraphQL, and Webhooks.
  
• Experience implementing authentication flows.
  
• Proficiency in SQL and BigQuery.
  
• Experience with orchestration frameworks (e.g., Airflow, Prefect) to manage and monitor complex workflows.
  
• Familiarity with containerization (Docker, Kubernetes) and cloud infrastructure (GCP/AWS) to deploy and scale workloads.
  
• Strong grounding in infrastructure as code (Terraform, Pulumi, CloudFormation) for repeatable, auditable environments.
  
• Ability to drive rapid development while ensuring maintainability, balancing short-term delivery with long-term platform stability.

• Deep understanding of authentication mechanisms (OAuth 2.0, API keys, secrets management) and secure multi-tenant architectures.
  
• Experience designing and operating high-availability, distributed systems in cloud environments.
  
• Exposure to event-driven architectures and real-time data processing tools.
  
• Knowledge of data governance, compliance (GDPR, SOC2), and security best practices.
  
• Experience working in a multi-tenant SaaS or data-intensive environment at scale.