Data Engineer

• Build and maintain ETL pipelines that ingest, clean, and aggregate data received from external vendors and large enterprise partners
• Develop Python‑based data processing workflows deployed on AWS cloud services
• Work with tools such as AWS Glue, Airflow, dbt, and PySpark to support data transformations and pipeline orchestration
• Help modernize existing workflows and assist in the gradual migration away from a legacy data system
• Collaborate with internal stakeholders to understand data needs, define requirements, and ensure reliable integration of partner data feeds
• Troubleshoot pipeline issues, optimize performance, and improve overall system stability
• Contribute to best practices around code quality, testing, documentation, and data governance

• 5+ years of hands-on data engineering experience (flexible for exceptional mid-level talent)
• Strong expertise in Python and SQL for data manipulation, automation, and backend data workflows
• Experience building ETL pipelines and working with data coming from external organizations or third-party sources
• Familiarity with AWS data technologies such as Glue, RDS, Lambda, or related cloud‑native services
• Experience with Airflow or dbt for orchestration (either is fine
• both are a plus)
• Background with PySpark or distributed data processing is highly desirable
• Any exposure to supporting or migrating off legacy systems is a strong plus
• Ability to work autonomously in a remote-first environment and communicate clearly with technical and non-technical colleagues

Exposure to supporting or migrating off legacy systems

• medical
• vision
• dental
• life and disability insurance
• 401(k) plan