Software Engineer (Data Systems, Python)
Posted Updated
- 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
- 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 at Northbeam, you’ll work alongside product managers, product engineers, and business leaders to turn customer needs into reliable data pipelines and products
- You’ll be supported by engineers who have built these systems before, with room to take on more ownership as you grow into the team
- The work involves building, maintaining, and improving a labyrinth of integrations and transformations across a complex network of touchpoints
- The system is powered by data spanning numerous ad platforms, a variety of order management systems (Shopify, Amazon, and others), and our own real-time events collected as customers navigate their online stores
- This is a startup. The one thing that’s constant is change. To start with, you can expect to:
- Build and maintain data pipelines that ingest and transform data from a variety of sources, with an eye toward reliability and maintainability
- Develop and support APIs that enable secure, tenant-aware data integrations with external systems
- Work within event-driven and batch processing architectures to keep data fresh and consistent
- Contribute to API design and integration patterns that support both real-time and batch ingestion across different authentication mechanisms (OAuth, API keys, etc.)
- Add monitoring and alerting that surfaces data freshness issues, failures, and performance problems before customers notice them
- Improve existing data flows and transformations, weighing cost, efficiency, and speed of delivery in a cloud-native environment
- Partner with data engineering, infrastructure, and product teams to make our integration platform easier to extend and onboard new sources into
- You’ll work with great people who have done this many times before. You’ll teach them some new tricks, and pick up some old ones
- Curiosity, a bias toward shipping, and a real appetite for building data pipelines at scale are what matter most here
- Some exposure to orchestration frameworks such as Airflow, Dagster, or Prefect
- Experience building against REST APIs; familiarity with GraphQL or webhooks is a plus
- A track record of shipping steadily and asking good questions when the path isn’t obvious
- Willingness to work in a containerized environment (Docker)
- Solid working proficiency in Python
- Comfort with SQL and some exposure to a cloud data warehouse (BigQuery, Snowflake, Redshift, or similar)
- 3+ years of experience in data engineering, software engineering, or integration engineering, with exposure to ETL, APIs, or data pipeline work
- Experience implementing authentication flows (OAuth 2.0, API keys, secrets management)
- Familiarity with Kubernetes or other production deployment tooling
- Experience working with ERP systems, CRMs, CDPs, or other enterprise data tools and their APIs
- Exposure to event-driven architectures and real-time data processing tools
- Awareness of data governance and compliance considerations (GDPR, SOC 2)
- Experience in a multi-tenant SaaS or data-intensive environment
- We accept applications on an ongoing basis
- 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