Software Engineer, Data Systems (Python)

Northbeam

$140K — $155K *
US-AnywhereRemote in Canada
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 3+ years of experience in data engineering, software engineering, or integration engineering.
  • Proficient in Python and comfortable with SQL.
  • Experience building against REST APIs; familiarity with GraphQL is a plus.
  • Exposure to orchestration frameworks like Airflow or Dagster.
  • Willingness to work with containerization technology like Docker.

Responsibilities

  • Build and maintain data pipelines for varied data sources while ensuring reliability.
  • Develop APIs for secure, tenant-aware data integrations with external systems.
  • Utilize event-driven and batch processing architectures to maintain data consistency.
  • Contribute to API design that supports real-time integrations across various authentication methods.
  • Implement monitoring to catch data quality and performance issues in advance.
  • Optimize existing data flows and transformations in a cloud-native environment.
  • Work collaboratively with engineering, infrastructure, and product teams to enhance the integration platform.

Benefits

  • Equity package and comprehensive healthcare benefits (medical, dental, vision).
  • 401(k) plan with company contributions.
  • Flexible PTO policy alongside 12 company-paid holidays.
  • 12 weeks of paid parental leave.
  • $500 work-from-home stipend to enhance remote setups.
Full Job Description
About the Role

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.

Curiosity, a bias toward shipping, and a real appetite for building data pipelines at scale are what matter most here.
Your Impact

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.

If this sounds like your kind of chaos, we'd love to hear from you.
What You Bring
  • 3+ years of experience in data engineering, software engineering, or integration engineering, with exposure to ETL, APIs, or data pipeline work.
  • Solid working proficiency in Python.
  • Experience building against REST APIs; familiarity with GraphQL or webhooks is a plus.
  • Comfort with SQL and some exposure to a cloud data warehouse (BigQuery, Snowflake, Redshift, or similar).
  • Some exposure to orchestration frameworks such as Airflow, Dagster, or Prefect.
  • Willingness to work in a containerized environment (Docker).
  • A track record of shipping steadily and asking good questions when the path isn't obvious.
Bonus Skills & Experience
  • 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.


Base Salary Range

$140,000-$155,000 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.

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