Data Engineer, Rightway

• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent work experience
• 5+ years of industry experience as a data engineer
• Expert-level SQL skills, including query optimization, schema design, and working with large-scale datasets in production environments
• Strong Python proficiency with experience writing and maintaining production-grade code
• Skilled in working with AWS systems in a production environment
• Experienced in scaling data infrastructure to handle high volumes of data
• Demonstrated ability to incorporate AI tools (e.g. GitHub Copilot, LLM-assisted development) into an engineering workflow to improve speed and quality

Desirable

• We are seeking a full-time Data Engineer III to join our team and define and deploy mission-critical data infrastructure
• The primary responsibility for this role is defining the processing of large healthcare datasets, which enable Rightway to generate insights that improve the health of more than 3 million members
• In this role, you will bring deep expertise in SQL and Python to build and maintain production-grade data pipelines within the AWS ecosystem — and you will leverage AI tooling to augment your workflow, accelerate development, and continuously improve the reliability and efficiency of our data platform
• While familiarity with medical data is beneficial, it is not a requirement
• Write production-level Python and SQL code, with a strong emphasis on complex SQL for data transformation, pipeline logic, and analytical query optimization
• Leverage AI tools and large language models to augment engineering workflows — from code generation and query optimization to automated testing, documentation, and process improvement
• Utilize AWS services such as Lambda, Glue, and Fargate for scalable data operations
• Build and maintain large-scale data pipelines using Apache Airflow
• Oversee the maintenance of Extract, Load, and Transform (ELT) processes using DBT
• Design optimized database schemas in PostgreSQL and Amazon Redshift to ensure data integrity and high performance
• Identify opportunities to apply AI-driven automation to repetitive or high-volume data engineering tasks, reducing manual effort and improving throughput