Clinical Data Architect

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve – we care.

What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow’s health today, we want to hear from you.

McKesson is a leading healthcare organization dedicated to improving patient outcomes through innovative solutions. We are seeking a highly skilled Clinical Data Architect to join our team and play a pivotal role in shaping our data infrastructure and our analytics capabilities.

The Clinical Data Architect is responsible for designing, implementing, and maintaining the data and data architecture that supports McKesson’s industry-leading products, clinical operations and research initiatives for Ophthalmology. The ideal candidate will have a strong technical background in cloud-based data pipelines, expertise in data & architecture for clinical data management, extensive experience using PostgreSQL, and a passion for leveraging data to drive healthcare improvements and innovation. The ideal individual will also have a drive for performance improvement and innovation using both traditional and non-traditional methods.  The ideal candidate is comfortable at the command line, but can also lead a technical team to scale and grow.

Key Responsibilities
LEAD TECHNICAL DATA EFFORTS

• Design, develop, and maintain robust data architectures to support clinical data integration,  products, and analyses.

• Collaborate with clinical, product and IT teams to understand data requirements and translate them into effective data models and solutions.

• Lead data integration efforts from start to finish, through the entire data life cycle (i.e. prototype to production, and data  ingestion to product usage and archival) for multiple electronic medical record (EMR) and practice management (PM) systems.

• Collaborate with the larger team to design, evolve and implement data architecture(s), infrastructure, data collection efforts and improvements to existing scale, processes and approaches.

• Establish monitoring solutions to prevent outages, to promote timely and accurate data collection, ingestion, processing and analysis.

BUILD CAPACITY & LEAD DATA TEAM

• Design architecture for infrastructure changes for highly performant, scalable, maintainable data pipelines; oversee implementation; test and characterize performance before moving to production.

• Lead a team of  integration specialists, developers and database administrators to ensure timely and accurate completion of data integration projects.

• Write and optimize complex SQL queries using PostgreSQL to extract, transform, and load (ETL) clinical data; mentor team to increase team capacity and skills.

• Provide technical leadership and mentorship to technical junior colleagues.

• Conduct code reviews to promote readability, reuse, performance and security; author code as appropriate and needed.

ENSURE DATA QUALITY & PERFORMANCE

• Create, manage, and monitor data quality metrics as part of the Clinical Data Quality Program.

• Use statistics and tools to evaluate data, present to leadership and stakeholders, and identify problems proactively.

• Ensure the quality and integrity of clinical data, with a particular emphasis on ophthalmology / retina data.

• Work to ensure proper data quality is maintained across all clinical data systems and that supporting products get the high quality data they need, when they need it.

• Develop and maintain documentation for data architecture, data flows, and data models.

• Ensure data products are produced on time with high quality, accuracy and integrity 

SUPPORT USERS OF THE DATA

• Support the people who use the data, both internally and externally, via tracing and  troubleshooting data issues, implementing resolutions, and promoting data transparency, leveraging AI tools as appropriate.

• Promote and evolve data transparency

• Use service tickets for all work, and ensure work is properly documented; verify and approve the work of the team as needed.  Serve as the final approval of moves to production.

• Ensure database performance such that that data are accessible and available on-time to analysts, products, support person