Verantos

• Help shape how clinical data is transformed and made usable for research by leading efforts in knowledge management, semantic normalization, and data quality. • Collaborate with clinicians, scientists, data scientists, product managers, and engineers to define scalable approaches for mapping clinical concepts. • Identify where and how key concepts can be captured. • Develop concept lists for cohort creation. • Design clinical data quality checks to ensure datasets meet clinical expectations. • Create and maintain concept groups. • Review customer code lists and recommend updates as needed. • Map claims data and health system data to standard concepts in the OMOP Common Data Model (CDM). • Semantically normalize CDM-converted data coming from multiple different health systems and map high priority unmapped concepts. • Create documentation on how to best use data to generate insights. • Collaborate with customers to help them understand how to leverage data to answer research questions. • Define disease-area–specific data quality testing processes. • Determine how to best capture concepts needed to answer customer research questions and analyze prevalence of concepts for feasibility assessments. • Specify annotation projects to capture complex clinical ideas.

• Lead the design and evolution of the data platform architecture, establishing patterns and standards the team builds on. • Build and operate production-grade data pipelines that ingest and transform high-variance, real-world clinical data reliably and at scale. • Design for automation from the start: pipelines that detect problems, recover gracefully, and surface issues without requiring manual intervention to run. • Contribute to quarterly data product releases, working closely with product, clinical, customer success teams to meet commitments. • Build data quality tests that reflect the evolving needs of our downstream consumers. • Mentor and elevate other data engineers through code review, architecture decisions, and shared standards. • Actively use and advocate for AI tools that improve the team's development velocity and code quality.

• Simplify and maintain the CI/CD pipelines for a multi-project monorepo, ensuring they are predictable, fast, and operable by the broader engineering team without specialized knowledge. • Plan and execute infrastructure changes incrementally, with clear rollout steps, validation strategies, and rollback plans that are communicated to the team before work begins. • Build and maintain operational documentation, runbooks, monitoring, and alerting that enable other engineers to independently troubleshoot and respond to production issues. • Collaborate with DevOps teammates across the organization to align on shared infrastructure standards including network design, permissions models, and deployment patterns. • Contribute directly to application code in Python and Typescript when platform concerns cross into the application layer, such as database performance, service configuration, or integration points. • Partner with QA to ensure infrastructure changes are properly tested and that the team has confidence in what's being shipped to each environment. • Actively use and champion AI tools to accelerate infrastructure and developer experience work.