Program Manager/Data Architect

Job Title: PROGRAM MANAGER/Data Architect
Location: San Francisco, CA, Onsite

Job summary: IT Data Leader drives business value from Data, Analytics, AI, and GenAI across the organization, acting as a trusted advisor who identifies and prioritizes high-impact initiatives, aligns stakeholders across business and IT, scales the Data Product model with Design Thinking and business-led governance, and provides technical leadership on scalable, AI-ready data solutions in partnership with Architecture and Engineering teams.

Experience: 9to13Yrs



Required Skills: Project Management

Responsibilities:

Core Job Responsibilities

Strategic Business Partnership and Cross-Functional Alignment

• Act as a trusted Data and Analytics leader, helping business functions identify opportunities to leverage data, analytics, AI, and GenAI for measurable outcomes.
• Build strong relationships across Commercial, Marketing, R&D, Quality, Operations, Supply Chain, and Finance to understand priorities and challenges.
• Translate business needs into actionable Data, Analytics, AI, and Data Product initiatives, and lead cross-functional discussions to drive alignment and decision-making.

Data Product Leadership and Design Thinking

• Establish and scale the Data Product delivery model across the organization.
• Champion product-centric ways of working and support adoption of Data Product principles across business domains.
• Partner with stakeholders to define, prioritize, and govern Data Products, driving discovery, roadmap development, and value realization through KPIs.
• Promote reusable, governed Data Products and support Data Mesh principles through domain-based ownership.

Data Engineering and Platform Excellence

• Champion modern data engineering principles and best practices.
• Build strong data foundations with clear standards for data quality, observability, metadata management, lineage, and security.
• Partner with Architecture and Engineering teams to ensure enterprise data assets are scalable, reliable, and optimized for analytics and AI.
• Champion effective use of Databricks and lakehouse technologies to support Data Products, Analytics, AI, and GenAI workloads.

Technical Leadership, Solution Design, and Architecture Alignment

• Provide technical leadership across Data, Analytics, AI, and Data Product initiatives from concept through delivery.
• Lead solution design, translating business requirements into scalable capabilities.
• Partner with Enterprise Architecture and Corporate IT to shape solution strategy and technology direction.
• Evaluate trade-offs between business value, scalability, and feasibility, ensuring solutions are secure, governed, and reusable.

AI and Generative AI Leadership

• Lead identification and assessment of AI and GenAI opportunities across the organization.
• Partner with stakeholders to define value-driven use cases and success metrics.
• Evaluate opportunities for strategic value, feasibility, and alignment with legal, privacy, and cybersecurity requirements.
• Collaborate with Legal, Privacy, Cybersecurity, Data Science, Engineering, and Delivery teams to support implementation.
• Promote responsible AI practices and monitor business impact.

Portfolio Prioritization and Demand Management

• Drive delivery of Data, Analytics, AI, and Data Product initiatives in partnership with Corporate IT, Architecture, and business stakeholders, ensuring commitments are met on time and within budget.
• Lead intake, evaluation, and prioritization of initiatives.
• Facilitate investment trade-off discussions and maintain visibility into progress, risks, and dependencies.
• Provide portfolio recommendations to leadership.

Business-Led Data Governance and Stewardship

• Champion a business-led governance model that promotes ownership and accountability for critical data assets.
• Establish data stewardship and quality practices across business domains.
• Promote metadata management, cataloging, and compliance best practices to strengthen trust and usability of enterprise data.
• Advocate for trusted, governed, AI-ready data assets that support strategic objectives.