Sr. Manager, Data Engineering

Sr. Manager, Data Engineering Remote | San Diego, California, United States Information Technology (IT) At Veracyte, we offer exciting career opportunities for those interested in joining a pioneering team that is committed to transforming cancer care for patients across the globe. Working at Veracyte enables our employees to not only make a meaningful impact on the lives of patients, but to also learn and grow within a purpose driven environment. This is what we call the Veracyte way – it’s about how we work together, guided by our values, to give clinicians the insights they need to help patients make life-changing decisions. Our Values: - We Seek A Better Way : We pursue bold ideas, embrace complexity, and keep pushing forward. - We Make It Happen : We act with urgency, deliver with excellence, and always find a way. - We Are Stronger Together : We engage with empathy, align around what's best for Veracyte, and celebrate as one team. - We Care Deeply : We show up with integrity, kindness, and respect for one another. The Position The Senior Manager, Data Engineering will manage an engineering team responsible for building and operating Veracyte’s enterprise data platforms. This role combines people leadership with direct technical ownership and is suited for someone who can move comfortably between architecture, implementation details, production operations, and team development. You will guide the evolution of modern data lake and lakehouse environments, delivering trusted and actionable data to scientific, clinical, operational, and commercial teams. You will partner closely with data science, analytics, product, clinical, software engineering, Security, and IT to translate business and scientific needs into secure, scalable, and maintainable solutions. This position is based in our San Diego office with a hybrid working model or may be US remote.

- Manage and develop a team of data engineers, supporting talent planning, hiring, coaching, performance management, career development, and team effectiveness. - Remain close enough to the technical work to guide architecture, design reviews, code quality, troubleshooting, and key implementation decisions. - Collaborate with business and scientific stakeholders to translate requirements into platform capabilities, delivery plans, and measurable outcomes. - Help establish and maintain data platform standards, governance practices, architectural guidelines, and operational processes. - Make pragmatic architectural decisions using AWS services such as S3, Glue, Athena, Lambda, IAM, and CloudWatch, and related technologies such as Snowflake. - Support continuous improvement of engineering practices for CI/CD, automated testing, observability, lineage, documentation, security, privacy, and code quality. - Partner closely with cross-functional teams, including Analytics, Data Science, Product, Clinical, Laboratory, Software Engineering, Security, and IT, to support shared goals and initiatives. - Ensure data-platform security, regulatory compliance, privacy, and quality-management requirements are addressed through appropriate architecture, controls, tooling, documentation, and cross-functional collaboration. - Drive platform delivery and operational excellence, helping ensure solutions meet business needs, performance expectations, and production reliability requirements. - Balance delivery priorities, operational support, platform enhancements, technical debt reduction, vendor relationships, and resource considerations. - Evaluate emerging technologies and recommend adoption based on measurable improvements in maintainability, scalability, reliability, performance, security, and cost. - Communicate technical decisions, alternatives, risks, recommendations, and trade-offs clearly to stakeholders and leaders across multiple functions, and build shared understanding in complex or sensitive situations.