Sr. Manager, Data Engineering at Veracyte

Job description

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. Model collaborative, inclusive leadership by engaging the right stakeholders early, seeking diverse perspectives, committing to decisions, pursuing better solutions, and maintaining high standards for quality and responsible use of company resources. Who You Are Required Qualifications Bachelor’s degree in computer science, engineering, data science, information systems, or a related field, or equivalent practical experience. 8+ years of relevant experience in data engineering, software engineering, data platforms, or related fields. 5+ years of people-management experience, including responsibility for team objectives, work planning, performance management, development, and staffing decisions. Demonstrated experience leading a data engineering department or multiple related disciplines and delivering outcomes that affect broader functional or business priorities. Demonstrated experience designing, building, and operating production data pipelines and data platforms, including data lake or lakehouse architectures. Strong working knowledge of AWS services such as S3, Glue, Athena, Lambda, IAM, and CloudWatch, or comparable technologies. Hands-on proficiency with SQL and Python, with the ability to review code, evaluate technical designs, troubleshoot production problems, and guide implementation decisions. Experience with ETL/ELT frameworks, orchestration tools, distributed data processing, analytical data modeling, and reusable data products or shared platform capabilities. Practical experience implementing data quality, automated testing, observability, lineage, security, privacy, and regulatory controls. Experience establishing operational objectives, policies, procedures, work plans, schedules, and resource priorities for a technical team. Experience managing technical debt and operational risk while continuing to deliver business and product priorities. Proven ability to collaborate across engineering, scientific, product, clinical, business, Security, and IT teams, including the ability to influence and build alignment in complex situations. Strong communication skills, including the ability to explain technical decisions, alternatives, risks, and trade-offs clearly to technical and nontechnical audiences. Preferred Qualifications Experience in biotechnology, life sciences, diagnostics, healthcare, or another regulated data environment. Experience working in environments subject to medical device regulations and quality-management requirements. Experience working with scientific, clinical, laboratory, LIMS, or bioinformatics data. Familiarity with ML/AI data workflows and supporting MLOps platforms. Experience optimizing AWS data-platform cost, reliability, security, and performance. Experience developing reusable data products, shared platform capabilities, or domain-oriented data architectures. Knowledge of metadata management, data catalogs, and lineage platforms. Experience managing budget inputs, vendors, or resource planning for a data engineering or platform team. Experience helping a team scale its processes without introducing unnecessary bureaucracy. We know that great candidates may not meet every qualification listed. If this role excites you and you believe your experience can help us advance our mission, we encourage you to apply. For candidates based in our San Diego office , the range is $199,000- $220,000. For candidates based in our South San Francisco office , the range is $202,000- $258,000. For candidates that are Remote : $192,825 - $220,000 #LI-Hybrid The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to years of experience, skillset, geographic location, industry, education, etc. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units. Pay range $199,000 — $220,000 USD What We Can Offer You Veracyte is a growing company that offers significant career opportunities if you are curious, driven, patient-oriented and aspire to help us build a great company. We offer competitive compensation and benefits, and are committed to fostering an inclusive workforce, where diverse backgrounds are represented, engaged, and empowered to drive innovative ideas and decisions. We are thrilled to be recognized as a 2024 Certified™ Great Place to Work ® in both the US and Israel - a testament to our dynamic, inclusive, and inspiring workplace where passion meets purpose. About Veracyte Veracyte (Nasdaq: VCYT) is a global diagnostics company whose vision is to transform cancer care for patients all over the world. We empower clinicians with the high-value insights they need to guide and assure patients at pivotal moments in the race to diagnose and treat cancer. Our Veracyte Diagnostics Platform delivers high-performing cancer tests that are fueled by broad genomic and clinical data, deep bioinformatic and AI capabilities, and a powerful evidence-generation engine, which ultimately drives durable reimbursement and guideline inclusion for our tests, along with new insights to support continued innovation and pipeline development. For more information, please visit www.veracyte.com or follow us on LinkedIn or X (Twitter) . Veracyte, Inc. is an Equal Opportunity Employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status or disability status. Veracyte participates in E-Verify in the United States. View our CCPA Disclosure Notice If you receive any suspicious alerts or communications through LinkedIn or other online job sites for any position at Veracyte, please exercise caution and promptly report any concerns to careers@veracyte.com

Requirements

Must-haves

Bachelor’s degree in computer science, engineering, data science, information systems, or a related field, or equivalent practical experience.
8+ years of relevant experience in data engineering, software engineering, data platforms, or related fields.
5+ years of people-management experience, including responsibility for team objectives, work planning, performance management, development, and staffing decisions.
Demonstrated experience leading a data engineering department or multiple related disciplines and delivering outcomes that affect broader functional or business priorities.
Demonstrated experience designing, building, and operating production data pipelines and data platforms, including data lake or lakehouse architectures.
Strong working knowledge of AWS services such as S3, Glue, Athena, Lambda, IAM, and CloudWatch, or comparable technologies.
Hands-on proficiency with SQL and Python, with the ability to review code, evaluate technical designs, troubleshoot production problems, and guide implementation decisions.
Experience with ETL/ELT frameworks, orchestration tools, distributed data processing, analytical data modeling, and reusable data products or shared platform capabilities.
Practical experience implementing data quality, automated testing, observability, lineage, security, privacy, and regulatory controls.
Experience establishing operational objectives, policies, procedures, work plans, schedules, and resource priorities for a technical team.
Experience managing technical debt and operational risk while continuing to deliver business and product priorities.
Proven ability to collaborate across engineering, scientific, product, clinical, business, Security, and IT teams, including the ability to influence and build alignment in complex situations.

Nice-to-haves

Experience in biotechnology, life sciences, diagnostics, healthcare, or another regulated data environment.
Experience working in environments subject to medical device regulations and quality-management requirements.
Experience working with scientific, clinical, laboratory, LIMS, or bioinformatics data.
Familiarity with ML/AI data workflows and supporting MLOps platforms.
Experience optimizing AWS data-platform cost, reliability, security, and performance.
Experience developing reusable data products, shared platform capabilities, or domain-oriented data architectures.
Knowledge of metadata management, data catalogs, and lineage platforms.
Experience managing budget inputs, vendors, or resource planning for a data engineering or platform team.
Experience helping a team scale its processes without introducing unnecessary bureaucracy.
We know that great candidates may not meet every qualification listed. If this role excites you and you believe your experience can help us advance our mission, we encourage you to apply.
For candidates based in our San Diego office , the range is $199,000- $220,000.
For candidates based in our South San Francisco office , the range is $202,000- $258,000.

Application prep

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Benefits

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