Staff Software Engineer (Data Systems, Python)
Posted Updated
- Northbeam is fundamentally a data product - the whole company. We don’t sell shoes, 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
- Our data systems team is foundational and load-bearing, and this role sets its technical direction. As a Staff engineer, you’ll own the architecture of the integration and ingestion platform that the rest of the company builds on — deciding how we onboard new sources, where the abstractions live, and what “reliable” means in practice
- You’ll work across product, engineering, and with business leaders, and your judgment will shape what the team builds long after any individual project ships
- The work involves a labyrinth of integrations and transformations across a complex network of touchpoints, powered by data spanning numerous ad platforms, order management systems (Shopify, Amazon, and others), and our own real-time event collection
- Own the architecture of our ingestion and integration platform, setting the patterns that determine how quickly and safely we onboard new data sources
- Define technical direction for event-driven and batch processing across the company, and make the build/buy and migration calls that go with it
- Establish the standards for observability, data freshness, and failure handling that the data systems team works to — and hold the bar on them
- Lead design across team boundaries, working with data engineering, infrastructure, and product to keep platform decisions coherent
- Raise the ceiling of the engineers around you through design review, mentorship, and the code you write
- Identify the platform problems nobody has scoped yet, make the case for solving them, and drive them to completion
- Production depth with orchestration (Airflow or similar) and containerized infrastructure (Docker, Kubernetes)
- Experience mentoring engineers and elevating engineering practice across a team or org
- A track record of designing API-based ETL systems at scale — REST, GraphQL, webhooks, and the authentication and multi-tenancy concerns that come with them
- 8+ years of software or data engineering experience, including significant time owning the architecture of large-scale ingestion, ETL, or integration platforms
- Sound judgment about when to invest in platform durability and when to ship and move on
- Demonstrated technical leadership: setting direction, aligning engineers who don’t report to you, and improving how a team builds, not just what it ships
- Deep proficiency in Python, and strong SQL and cloud data warehouse experience (BigQuery or equivalent)
- 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
- 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