Software Engineer, Data Systems (Python)

northbeam; United States; Hybrid; USD 140,000 - 155,000; Full time

Benefits offered by this job

Equity package

Healthcare coverage

401(k) plan

Flexible PTO

Parental leave

Remote setup stipend

Job summary

Northbeam is hiring a data integration engineer to join a data systems team supporting a marketing intelligence platform for ecommerce brands. You will build, maintain, and improve a network of data pipelines and APIs across ad platforms, order systems, and first-party events, collaborating with product, data engineering, and infrastructure peers.

The role emphasizes reliability, security, and cloud-native practices with strong Python, SQL, and REST API skills.

Qualifications

• Two or more 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.
• Comfort with SQL and cloud data warehouses (BigQuery, Snowflake, or Redshift).
• Exposure to orchestration frameworks such as Airflow, Dagster, or Prefect.
• Willingness to work in a containerized environment using Docker.

Responsibilities

• Build and maintain data pipelines that ingest and transform data from a variety of sources with a focus on reliability and maintainability.
• Develop and support tenant-aware APIs that enable secure 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 supporting real-time and batch ingestion across authentication mechanisms like OAuth and API keys.
• Add monitoring and alerting that surfaces data freshness issues, failures, and performance problems before customers notice.
• Improve existing data flows and transformations, weighing cost, efficiency, and delivery speed in a cloud-native environment.
• Partner with data engineering, infrastructure, and product teams to make the integration platform easier to extend and onboard new sources into.

Skills

Python

REST APIs

SQL

ETL / Data pipelines

Airflow / Dagster / Prefect

Docker

GraphQL

Tools

Airflow

Dagster

Prefect

Docker

Kubernetes

BigQuery/Snowflake/Redshift

Job description

Role overview

This role sits on a data systems team that is foundational to a marketing intelligence platform serving e-commerce brands. The engineer will build, maintain, and improve a network of integrations and data pipelines spanning ad platforms, order management systems, and first-party events, partnering with product, data engineering, and infrastructure teammates.

Responsibilities

• Build and maintain data pipelines that ingest and transform data from a variety of sources with a focus on reliability and maintainability.
• Develop and support tenant-aware APIs that enable secure 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 supporting real-time and batch ingestion across authentication mechanisms like OAuth and API keys.
• Add monitoring and alerting that surfaces data freshness issues, failures, and performance problems before customers notice.
• Improve existing data flows and transformations, weighing cost, efficiency, and delivery speed in a cloud-native environment.
• Partner with data engineering, infrastructure, and product teams to make the integration platform easier to extend and onboard new sources into.

Requirements

• Two or more 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.
• Comfort with SQL and some exposure to a cloud data warehouse such as BigQuery, Snowflake, or Redshift.
• Some exposure to orchestration frameworks such as Airflow, Dagster, or Prefect.
• Willingness to work in a containerized environment using Docker.

Nice to have

• Familiarity with GraphQL or webhooks.
• Experience implementing authentication flows including OAuth 2.0, API keys, and secrets management.
• Familiarity with Kubernetes or other production deployment tooling.
• Experience working with ERP, CRM, CDP, or other enterprise data tools and their APIs.
• Exposure to event-driven architectures and real-time data processing.
• Awareness of data governance and compliance considerations such as GDPR and SOC 2.
• Experience in a multi-tenant SaaS or data-intensive environment.

Benefits and work setup

• Base salary range of $140,000–$155,000 USD, with variation based on experience, skills, and location.
• Equity package, comprehensive medical, dental, and vision benefits, and a 401(k) plan.
• Flexible PTO, 12 company-paid holidays, and 12 weeks of paid parental leave.
• $500 work-from-home stipend to support a remote setup.
• Remote-friendly company with physical offices in San Francisco and Los Angeles.
• Interview process typically spans 5–7 interviews over roughly 5–8 hours.