Staff Software Engineer, Data Systems (Python) at Northbeam

Job description

About Northbeam Northbeam is building the world's most advanced marketing intelligence platform, providing top eCommerce brands a unified view of their business data through powerful attribution modeling and customizable dashboards. Our technology helps customers accurately track ad spend, understand the full customer journey, and drive profitable growth. Machine learning has been at the heart of Northbeam since day one: our full suite of measurement, spanning multi-touch attribution, MMM+, and incrementality, is built on it, along with laser-accurate first-party data. Now we're taking that foundation further, using AI to help brands operationalize their data and turn Northbeam insights into automated decisions. 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. We're a remote-friendly company with physical offices in San Francisco and Los Angeles. About the Role 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. Your Impact 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. What You Bring 8+ years of software or data engineering experience, including significant time owning the architecture of large-scale ingestion, ETL, or integration platforms. Deep proficiency in Python, and strong SQL and cloud data warehouse experience (BigQuery or equivalent). 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. Production depth with orchestration (Airflow or similar) and containerized infrastructure (Docker, Kubernetes). Demonstrated technical leadership: setting direction, aligning engineers who don't report to you, and improving how a team builds, not just what it ships. Experience mentoring engineers and elevating engineering practice across a team or org. Sound judgment about when to invest in platform durability and when to ship and move on. Bonus Skills & Experience 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. #LI-Remote Base Salary Range $190,000 — $220,000 USD Actual compensation may vary based on experience, skills, and location. In addition to your base salary, we offer an equity package, comprehensive healthcare benefits (medical, dental, and vision), and a 401(k) plan. Our team enjoys a flexible PTO policy, 12 company-paid holidays, and 12 weeks of paid parental leave. We also provide a $500 work-from-home stipend to support your remote setup. Interview Process 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.

Requirements

Must-haves

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.
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.
8+ years of software or data engineering experience, including significant time owning the architecture of large-scale ingestion, ETL, or integration platforms.
Deep proficiency in Python, and strong SQL and cloud data warehouse experience (BigQuery or equivalent).
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.
Production depth with orchestration (Airflow or similar) and containerized infrastructure (Docker, Kubernetes).
Demonstrated technical leadership: setting direction, aligning engineers who don't report to you, and improving how a team builds, not just what it ships.
Experience mentoring engineers and elevating engineering practice across a team or org.
Sound judgment about when to invest in platform durability and when to ship and move on.
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.

Nice-to-haves

Bonus Skills & Experience

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Keywords to mirror

machine learningairestgopythonsqlapigraphqldockerkubernetes

Platform: greenhouse
Effort: quick

Benefits

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Dental

Vision

401(K)

Pto

Parental Leave