Software Engineer, Data Systems (Python)

Team: IT

Location: US

Commitment: Full-time

Workplace Type: remote

Accountabilities:

• Build and maintain reliable, maintainable data pipelines that ingest and transform information from a wide range of external and internal sources.
• Develop and support secure, tenant-aware APIs and integrations with external systems.
• Work with both event-driven and batch processing architectures to maintain fresh, consistent, and reliable data.
• Contribute to API design and integration patterns supporting real-time and batch ingestion across authentication methods such as OAuth and API keys.
• Implement monitoring and alerting systems that identify data freshness issues, failures, and performance problems before they affect customers.
• Improve existing data flows and transformations while balancing infrastructure costs, efficiency, reliability, and speed of delivery.
• Partner with data engineering, infrastructure, and product teams to make the integration platform easier to extend and onboard new data sources.
• Help evolve a complex network of integrations and transformations spanning advertising platforms, order management systems, and real-time customer events.
• Contribute to the scalability and maintainability of data systems within a cloud-native and containerized environment.

Requirements:

• 3+ years of experience in data engineering, software engineering, integration engineering, or a related field, with exposure to ETL, APIs, or data pipeline development.
• Solid working proficiency in Python.
• Experience building and integrating REST APIs; familiarity with GraphQL or webhooks is a plus.
• Comfortable working with SQL and with some exposure to cloud data warehouses such as BigQuery, Snowflake, Redshift, or similar.
• Experience or exposure to orchestration frameworks such as Airflow, Dagster, or Prefect.
• Willingness to work in a containerized environment using Docker.
• Experience implementing authentication flows such as OAuth 2.0, API keys, or secrets management is a plus.
• Familiarity with Kubernetes or other production deployment technologies is a plus.
• Experience working with ERP systems, CRMs, CDPs, or other enterprise data platforms and their APIs is valuable.
• Exposure to event-driven architectures and real-time data processing tools is a plus.
• Awareness of data governance and compliance considerations, including GDPR and SOC 2, is beneficial.
• Experience in a multi-tenant SaaS or data-intensive environment is a plus.
• Demonstrated ability to ship consistently, work independently, and ask thoughtful questions when requirements or solutions are not immediately clear.
• Strong curiosity, problem-solving ability, and a practical bias toward building and delivering reliable solutions.
• Must be authorized to work in the United States or Canada; the role may require immigration sponsorship depending on individual circumstances.

Benefits:

• Base salary range of $140,000–$155,000 USD.
• Equity package in addition to base salary.
• Comprehensive medical, dental, and vision healthcare benefits.
• 401(k) retirement plan.
• Flexible paid time off policy.
• 12 company-paid holidays.
• 12 weeks of paid parental leave.
• $500 work-from-home stipend to support a remote working setup.
• Fully remote work arrangement.
• Opportunity to work on large-scale data systems, integrations, and data-intensive SaaS products.
• Collaboration with experienced engineers across data, infrastructure, and product functions.
• Opportunities to take on increasing ownership as the data systems team and platform evolve.