Software Engineer, Data Systems (Python)

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.