Guardant Health is a leading precision oncology company focused on guarding wellness and giving every person more time free from cancer. Founded in 2012, Guardant® is transforming patient care and accelerating new cancer therapies by providing critical insights into what drives disease through its advanced blood and tissue tests, real-world data and AI analytics. Guardant tests help improve outcomes across all stages of care, including screening to find cancer early, monitoring for recurrence in early-stage cancer, and treatment selection for patients with advanced cancer. comand follow the company onLinkedIn,X (Twitter)andFacebook.
Are you passionate about transforming healthcare through data-driven innovation The Enterprise Data Platform team is seeking a hands-on Data Engineering Manager to lead the design, evolution, and scaling of our AWS-based enterprise data platform that powers analytics, operational intelligence, AI-enabled solutions, and business-critical decision-making. This role is ideal for a technical leader who combines strong data engineering expertise with architectural vision, product thinking, and a passion for solving business problems through data. As a player-coach, you will contribute to architecture, technical design, and key implementations while mentoring engineers and shaping the future of our data platform. You will partner closely with Engineering, Product, Analytics, Operations, and business stakeholders to build scalable data products and platform capabilities that transform data into actionable insights, intelligent automation, and measurable business outcomes. Architect and evolve scalable, secure, and AI-ready data platforms across ingestion, storage, transformation, analytics, and data product layers.
Define technical vision, architecture standards, and engineering best practices that balance business needs, scalability, governance, and innovation. Collaborate across Engineering, Product, Analytics, Operations, and business teams to define and execute the architectural vision for a modern data platform, influencing long-term technical direction while balancing current priorities with future growth.
Lead the evolution of our AWS-centric data platform by continuously evaluating modern data architecture patterns, cloud-native services, and emerging AI technologies to ensure the platform scales efficiently with growing business needs and data volumes.
Champion modern data architecture patterns including data products, data contracts, observability, self-service capabilities, metadata-driven architectures, and AI-assisted engineering practices.
Data Products & Business Impact
Lead the design and delivery of data products that generate measurable business value through analytics, automation, AI/ML, and operational insights.
Apply a product mindset to data solutions, ensuring investments align with business priorities and user needs.
Define success metrics and drive adoption, reliability, and business outcomes for data products.
Engineering Leadership
Lead the design and evolution of scalable data platforms and engineering practices that enable reliable delivery of data products across analytics, AI/ML, and operational use cases.
Guide technology, architecture, and engineering decisions across the data ecosystem to ensure scalability, maintainability, operational excellence, and long-term platform evolution.
Establish engineering standards for building reliable, scalable, and maintainable data platforms across batch, streaming, analytics, and AI-enabled workloads.
Contribute to architecture reviews, design discussions, code reviews, and critical implementations.
Promote engineering excellence through automation, testing, observability, CI/CD, Infrastructure-as Code, and operational best practices.
Hire, mentor, and develop a high-performing team of data engineers.
Coach engineers in system design, architectural thinking, engineering craftsmanship, and operational excellence.
Ensure strong foundations in data quality, lineage, governance, privacy, security, and compliance.
Partner with security and governance teams to implement best practices for handling sensitive and regulated data.
8+ years of experience in Data Engineering, Data Platform Engineering, Analytics Engineering, or related fields.

2+ years of experience leading and growing engineering teams.
Proven experience building and scaling enterprise data platforms and data products.
Demonstrated experience delivering measurable business value through data engineering, analytics, AI/ML, automation, or a combination of these capabilities.
Strong expertise in data architecture, data modelling, distributed data processing, and modern data platform technologies.
Experience with technologies such as Spark, Kafka, Airflow, cloud-native services, and modern data engineering frameworks.
Experience designing, building, and operating enterprise-scale data platforms on AWS, including data lake, data warehouse, orchestration, streaming, and analytics services.
Experience with AWS technologies such as S3, Redshift, Glue, Lambda, Kinesis, IAM, Lake Formation, and related platform services.
Proven ability to translate complex business challenges into scalable technical solutions and data products.
Experience building AI-enabled data products and intelligent automation solutions.

Experience applying machine learning, predictive analytics, Generative AI, or LLM-enabled capabilities to solve business problems.
Experience with modern analytics engineering practices and tools such as dbt. Experience with streaming and real-time data architectures.
Experience leading modernization of AWS-based data platforms and evaluating emerging technologies to improve scalability, reliability, governance, and developer productivity.
Experience with modern data stack technologies such as dbt, DataZone, Iceberg, Delta Lake, or similar ecosystem tools.
Experience in healthcare, life sciences, or other regulated industries. Experience working with HIPAA, GDPR, PII, or other regulated datasets. Advanced degree in Computer Science, Engineering, Data Science, or a related technical field.
AI & Digital Fluency
~ Demonstrate curiosity, sound judgment, and the ability to critically evaluate and responsibly leverage AI-enabled tools in accordance with company policies, ethical standards, and regulatory requirements to improve the efficiency, effectiveness, and quality of work.

Within the range, individual pay is determined by work location and additional factors, including, but not limited to, job-related skills, experience, and relevant education or training. Employee may be required to lift routine office supplies and use office equipment. Majority of the work is performed in a desk/office environment; Guardant Health is committed to providing reasonable accommodations in our hiring processes for candidates with disabilities, long-term conditions, mental health conditions, or sincerely held religious beliefs. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.

Manager, Data and Analytics Engineering

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