Software Engineer, Data Systems (Python)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Software Engineer, Data Systems (Python) based in United States. The Software Engineer, Data Systems (Python) will help build and evolve the data infrastructure behind a sophisticated marketing intelligence platform. You will develop reliable data pipelines, integrations, and transformation systems that bring together information from advertising platforms, commerce systems, and real-time customer events. Working closely with product, data engineering, infrastructure, and business teams, you will turn customer needs into scalable and dependable data products. The role combines software engineering with a strong data focus, covering both batch and event-driven architectures. You will have the opportunity to improve reliability, observability, performance, and scalability across a complex integration ecosystem. As part of a fast-moving startup environment, you will be encouraged to ship consistently, ask thoughtful questions, and take increasing ownership of critical systems. You will also work alongside experienced engineers while contributing your own ideas and helping evolve the platform as it grows. 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.