Data Engineer

Role overview Build and maintain data pipelines that support operational processes and reporting for internal teams and customers. This role suits an engineer with a few years of experience who is ready to take on more end-to-end ownership, contribute reusable engineering components, and help keep production data reliable.

Responsibilities - Develop and maintain production data pipelines used by teams and customers. - Connect systems through internal and external APIs to exchange data. - Orchestrate and automate workflows with Airflow running on Kubernetes. - Add unit tests, monitoring, and alerts to protect pipeline reliability. - Improve the efficiency and observability of existing data workflows. - Monitor production, investigate failures, document causes, and clarify requirements with stakeholders. - Join design discussions and identify functional gaps early.

Requirements - At least 3 years of data engineering experience and 3 years working with Airflow. - Proficiency in Python and SQL. - Working knowledge of Snowflake, Airflow, dbt, and Google Cloud Platform. - A bachelor’s degree in computer science or a related field.

Nice to have Experience in fintech, payments, or a related sector, and experience administering Airflow.

Benefits and work setup This is a remote role for candidates located in the United States; applicants must already be authorized to work there without sponsorship or transfer. Benefits include medical, dental, and vision coverage, stock options, a retirement plan, a monthly home-office stipend, paid parental leave, flexible time off, sick and safe time, and paid holidays.