• Evaluate and improve data quality, completeness, and consistency across 30+ databases, applications, platforms, and APIs. • Design and build Scorpion's analytical data platform, creating a trusted source of truth for business and client data. • Develop and maintain scalable data pipelines that efficiently move data from operational systems into the analytical platform. • Help teams transition from querying production databases directly to using trusted analytical data sources. • Design data access patterns that enable AI agents and applications to quickly retrieve relevant client and business information. • Build secure, scalable solutions that deliver client context and business insights to internal applications and AI-powered experiences. • Define, monitor, and improve service level agreements (SLAs) for data freshness, availability, reliability, and performance. • Partner with engineering, product, and data science teams to establish data standards, governance practices, and data contracts. • Continuously improve the scalability, performance, and reliability of Scorpion's data ecosystem.

• Apply advanced technical knowledge and enterprise-focused thinking using AI and automation • Serve as a technical leader who coaches team members and influences business requirements • Identify innovative reusable solutions and develop strategic data solutions • Create advanced automated frameworks and design platform features • Use storytelling techniques to build consensus across diverse stakeholder groups • Mentor junior and intermediate data engineers on advanced technical concepts • Influence business and regulatory requirements through technical expertise and strategic recommendations • Drive organizational value through strategic data engineering initiatives and AI implementation

• Lead and mentor a team of data engineers, fostering a culture of continuous learning, innovation, and operational excellence. • Partner with cross-functional teams to design and implement scalable data pipelines and models aligned with business needs and industry best practices. • Oversee the development, deployment, and maintenance of enterprise-grade ELT processes, data marts, and business intelligence assets. • Own and evolve data quality frameworks, ensuring proactive monitoring, troubleshooting, and resolution of data issues. • Champion the adoption of automation and modern data engineering practices, driving efficiencies in pipeline management and data delivery. • Guide your team in building domain knowledge around healthcare operations, ensuring data solutions comply with regulatory and security requirements. • Contribute to strategic planning for the data engineering function, including resource allocation, technology selection, and process improvement initiatives. • Support and enforce software development best practices, including code reviews, source control, CI/CD, and testing.

• Use data engineering best practices to produce high quality, maximally available data models which are intuitive to data analysts and trusted by stakeholders • Develop deep domain knowledge in healthcare operations, tracking regulatory developments related to analytics products you maintain • Apply quality measures and other metrics to datasets originating from internal and external clients • Build scalable ELT pipelines and business intelligence dashboards as needed, embracing automation wherever possible • Implement data quality checks which proactively identify data issues and distributional shifts to ensure accuracy of downstream analytical products