Senior Software Engineer (Data Systems, Python)
Posted Updated
- Northbeam is fundamentally a data product - the whole company. We don’t sell shoes, ads, games, or database technologies. We sell data: quality integrations with a variety of platforms, fresh and reliable data pulls, correct aggregations, and algorithmic insights on top of that data, all packaged up in a user-facing application
- What this means is that out data systems team is foundational and load-bearing. As a data-tilted software engineer working at Northbeam, you will work with a cross-functional team of product managers, product engineers, and business leaders to translate our customers’ feedback into scalable data pipelines and products
- The work involves creating, maintaining, and improving a labyrinth of integrations and transformations in a complex network of touchpoints to keep everything running smoothly. The system is powered by data that spans numerous ad platforms, a variety of order management systems (such as Shopify and Amazon), as well as our own real-time events that we collect as our customers navigate their online stores
- Curiosity, experience, and a desire to build data pipelines and applications at scale will be the key to success in this role
- 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
- Experience with API-based ETL, handling REST, GraphQL, Webhooks
- Familiarity with containerization (Docker, Kubernetes) to deploy and scale workloads
- Proficiency in SQL and BigQuery
- Experience with orchestration frameworks (e.g., Airflow) to manage and monitor complex data workflows
- Strong proficiency in Python
- Ability to drive rapid development while ensuring maintainability, balancing short-term delivery needs with long-term platform stability
- 5+ years of experience in data engineering, software engineering, or integration engineering, with a focus on ETL, APIs, and data pipeline orchestration
- Experience implementing authentication flows
- 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
- The interview process varies by role but typically begins with a 30-minute interview with a Northbeam recruiter, followed by a video interview with the hiring manager
- Next, candidates complete a role-specific video interview followed by video or onsite interviews with several team members. The final step is a video interview with our CEO/Co-founder. The entire interview process is usually 5-7 interviews total and requires around 5-8 hours of your time
- We accept applications on an ongoing basis