Role Summary
Senior Director of Data and AI Architecture to lead strategic data architecture initiatives across the enterprise, focusing on Data and AI enablement and digital transformation. Serves a key role in the cloud migration initiative to transform enterprise data architecture into a modern, cloud-native ecosystem. This position can be 100% remote but must be located in the United States.
Responsibilities
- Central accountability to implement responsible Data and AI practices that comply with evolving regulations and Dynavax ethical principles.
- Lead efforts to streamline data processes, improve data quality and consistency, and enable more efficient analytical capabilities across the organization.
- Build an AI-ready data foundation to leverage machine learning and AI to enhance business decision-making across all domains.
- Advise the Dynavax Data and AI committee on AI solutions, investments and benefit analysis (e.g. ROI).
- Collaborate across the business and IT, demonstrating excellent communication and stakeholder management skills.
- Help improve data and AI literacy across the organization.
Qualifications
- Required: Bachelor’s degree in computer science, engineering, or related technical field.
- Required: 8+ years of experience in enterprise data architecture or systems design.
- Required: Strong knowledge of AI operating model and data governance, lineage, and metadata management principles.
- Required: Ability to establish data governance councils, stewardship, and quality frameworks.
- Required: Proven experience with large-scale data migration projects and cloud transformation.
- Required: Deep understanding of enterprise architecture frameworks and methodologies.
- Required: Familiarity with data operability standards (HL7/FHIR; CDISC; OMOP).
- Required: Strong technical background in database platforms (Databricks; Snowflake; Amazon Redshift).
- Required: Understanding of cloud architecture principles (AWS preferred).
- Required: Enterprise systems architecture.
- Required: AWS and cloud technologies.
- Required: Data modeling and design.
- Required: Data lineage and governance tools.
- Required: ETL/ELT processes.
- Required: Big data and analytics platforms.
- Required: Financial risk systems and methodologies.
- Required: Programming knowledge (Python, SQL, etc.).
- Required: DevOps and CI/CD principles.
- Required: Knowledge graph and semantic web technologies.
- Required: Machine learning operations (MLOps).
- Required: AI-focused data catalog tools.
- Required: Schema registry and metadata management systems.
- Required: Feature store architecture for machine learning.
- Required: Ability to influence executives and translate complex technical concepts for non-technical stakeholders.
- Required: Ability to sit for prolonged periods; reach with arms and hands; lift and move small objects; use hands to keyboard and perform other office related tasks including repetitive movement of the wrists, hands and/or fingers.
- Required: Occasional travel required, as needed.
- Preferred: Master’s degree in a related field.
- Preferred: Life Sciences/Pharma/Biotech experience.
- Preferred: Cloud platform certifications (AWS Certified Solutions Architect).
- Preferred: Enterprise Architecture certifications (TOGAF, Zachman).
- Preferred: Data Management certifications (CDMP, DAMA).
- Preferred: Project/Program Management certifications (PMP, Prince2, Agile/Scrum).
- Preferred: AI/ML certifications or specialized training.
- Preferred: Familiarity with GDPR, NIS2, EU AI Act.
Education
- Bachelor’s degree in computer science, engineering, or related technical field (Master’s preferred).
Additional Requirements
- Occasional travel required, as needed.
- Physical ability to sit for prolonged periods and perform typical office tasks.