Software Engineer, Data Systems (Python)

Summary

Northbeam is a marketing intelligence platform that provides eCommerce brands with unified business data, attribution modeling, and customizable dashboards. The Software Engineer, Data Systems will build and maintain reliable data pipelines, APIs, and integration systems while improving event-driven and batch data processing, monitoring, and cloud-native data flows.

Responsibilities

• 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

Skills

• 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
• 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

Qualifications

Must Haves

• 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

Nice to Haves

• 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

Benefits

• An equity package
• Comprehensive healthcare benefits (medical, dental, and vision)
• A 401(k) plan
• A flexible PTO policy
• 12 company-paid holidays
• 12 weeks of paid parental leave
• A $500 work-from-home stipend to support your remote setup