• Design, build, and maintain scalable data pipelines and ETL/ELT workflows • Help to own and improve our data warehouse architecture in Snowflake • Implement data modeling best practices to support analytics and reporting needs • Drive data quality initiatives, including validation, testing, and monitoring frameworks • Partner with product engineering teams to design data contracts and integrate data capture into applications • Work closely with Analytics and Business Intelligence teams to understand reporting needs and deliver reliable data products • Collaborate with Security and Compliance to implement data governance and privacy best practices • Partner with Product and Engineering leadership on data strategy and technical roadmaps • Collaborate with Clinicians and Clinical Researchers to ensure they have the data available to deliver on their projects and support patient care • Work with our Analysts to decrease latency, improve testability and integrate with de-identification providers to meet our goals and regulatory needs • Mentor and coach more junior data engineers, fostering growth and technical development • Establish and document data engineering standards, patterns, and best practices • Champion a culture of data quality, automation, and continuous improvement

• Collaborate with product managers and business stakeholders to understand complex business requirements to translate business needs into well-designed and maintainable solutions • Ensure data quality and reliability by implementing robust data quality checks, monitoring, and alerting to ensure the accuracy and timeliness of all data pipelines • Create data governance policies and develop data models and schemas optimized for analytical workloads • Influence the direction for key infrastructure and framework choices for data pipelining and data management • Manage complex initiatives by setting project priorities, deadlines, and deliverables • Collaborate effectively with distributed team members across multiple time zones, including offshore development teams • Build relationships and foster team cohesion across geographical and cultural boundaries

• Architects, designs, develops, implements and supports various components for the enterprise data warehouse and associated data sources. • Provides support for reporting projects, as well as process and architectural recommendations. • Mentors staff, demonstrates best practices, plans for business continuity and sustainability and works on projects that support Business Intelligence and Data Warehousing functions. • Develops data integration and transformation processes across on premise and cloud data sources using tools, including Oracle Data Integrator, Boomi Atmosphere, Informatica, as determined by the environment. • Works with the user community and reporting team to understand business data and data transformation requirements. • Converts requirements to functional and technical specifications for database and integration design. • Manages requests and/or components of larger projects with appropriate documentation and status reports. • Develops data models and database designs that leverage knowledge of data warehouse modeling best practices. • Provides leadership and serves as a subject matter expert. • Collaborates with other team members using scrum processes or other project management disciplines. • Follows best practices for change and code management. • Provides supporting technical documentation that is well written, organized and maintained. • Participates in ongoing stabilization, support and maintenance. • Provides on call support as needed for business continuity and operations. • Attends webinars, reads case studies and white papers, and participates in opportunities to further refine skills and stay apprised on functional area topics. • Maintains current knowledge of technology, equipment, and/or systems and advises on newer technologies.

• Work with the engineering team to create the data infrastructure • Maintain the data infrastructure in AWS • Work with the business users to understand their reporting requirements • Create reports and other forms of data access and visualization • Develop test infrastructure to maintain data integrity • Lead implementation of a BI system, such as Tableau • Create and maintain data-driven automation pipelines