Sr. IT Manager, Global Data and Analytics

Abbott • Alameda, CA

1d • Onsite

About The Position

The Senior IT Manager – Global Data and Analytics is a global leadership role responsible for accelerating business value through Data, Analytics, Artificial Intelligence (AI), and Generative AI (GenAI) across Abbott Diabetes Care. This role serves as a trusted strategic advisor to business leaders and a key member of the Global Data & Analytics organization, helping identify, shape, prioritize, and drive data, analytics, and AI initiatives that deliver measurable business outcomes. Working across Commercial, Marketing, R&D, Quality, Operations, Supply Chain, Finance, and other business functions, this leader serves as a critical connector between business stakeholders, Functional BRMs, the Global Data & Analytics organization, and Corporate IT teams, bridging business strategy with execution to ensure investments are aligned to strategic priorities and focused on value realization. A key aspect of this role is establishing and scaling ADC's Data Product delivery model, embedding Product and Design Thinking practices across the organization, and enabling business-led data governance. This leader will champion a product-centric approach to data, analytics, and AI while driving adoption of modern data engineering principles and capabilities to support trusted, scalable, and AI-ready data solutions. This leader will provide technical leadership and conceptual solution direction across Data, Analytics, AI, and Data Product initiatives, partnering with Architecture, Engineering, and Corporate IT teams to shape scalable solutions that align business priorities with enterprise technology capabilities. The ideal candidate combines strategic thinking, business acumen, deep technical data and analytics expertise, AI/GenAI knowledge, product management mindset, and strong stakeholder leadership to maximize the value of ADC's global data and analytics investments.

Requirements

• 10+ years of progressive experience in Data & Analytics leadership roles with strong foundations across Data Engineering, Data Architecture, Analytics, Data Management, and Data Governance.
• Demonstrated hands-on experience delivering enterprise-scale data and analytics solutions prior to moving into leadership roles.
• Proven experience partnering with senior business leaders and translating strategic priorities into scalable, technology-enabled solutions.
• Expertise in operating across business functions, Functional BRMs, Data & Analytics, Architecture, Engineering, and IT organizations within complex matrixed environments.
• Deep understanding of modern data architectures, cloud-based analytics ecosystems, enterprise data platforms, and product-oriented delivery models, including experience with technologies such as Databricks, Snowflake, Amazon Redshift, and related cloud data platforms.
• Strong experience with AWS cloud services and architectures supporting enterprise Data & Analytics platforms.
• Hands-on experience with Databricks , including Lakehouse architecture principles, Delta Lake, Unity Catalog, and modern data governance practices.
• Experience establishing and scaling Data Products, Data Product operating models, Data Mesh principles, domain-oriented ownership, and business-led data governance practices.
• Experience leading conceptual solution design and influencing architecture, platform, and technology decisions in partnership with Architecture and Engineering teams.
• Proven ability to lead through influence, drive alignment, and make decisions across complex global matrix organizations.
• Strong strategic thinking, business acumen, and problem-solving capabilities with the ability to balance business priorities, technical considerations, and long-term platform sustainability.
• Bachelor’s degree in information technology, Information Systems, Computer Science, Engineering, Data Analytics, Business, or a related field.

Nice To Haves

• Experience in the healthcare industry, including regulated environments involving patient, clinical, or healthcare data.
• Experience with enterprise analytics and business intelligence platforms, including Power BI, Tableau, Qlik Sense, or similar technologies, supporting self-service analytics, reporting, and data-driven decision making.
• Familiarity with modern GenAI and LLM frameworks, including experience with evaluating or implementing AI, Generative AI, and LLM-based solutions within enterprise environments.
• Exposure to applied AI/ML initiatives, including model governance, MLOps concepts, or responsible AI practices.
• Experience with Customer Data Platform (CDP) technologies.
• Exceptional communication, facilitation, stakeholder management, and executive presentation skills, with the ability to influence senior business executives, IT leadership, and cross-functional stakeholders.
• Master’s degree preferred.

Responsibilities

• Serve as a trusted Data & Analytics leader supporting business functions in identifying opportunities to leverage data, analytics, AI and GenAI to drive business outcomes.
• Build strong partnerships and trusted relationships across Commercial, Marketing, R&D, Quality, Operations, Supply Chain, Finance, and other business functions to understand priorities, challenges, and strategic objectives.
• Translate business priorities into actionable Data, Analytics, AI, and Data Product initiatives.
• Lead cross-functional discussions to drive prioritization, decision-making, and execution alignment across multiple stakeholder groups.
• Establish, scale and mature the Data Product delivery model across Abbott Diabetes Care.
• Champion product-centric ways of working and enable adoption of Data Product principles across ADC business domains.
• Partner with business stakeholders to identify, define, prioritize, and govern Data Products aligned that deliver measurable business outcomes.
• Drive Data Product discovery, visioning, roadmap development, and lifecycle management and value realization through KPIs and business impact.
• Promote reusable, scalable, and governed Data Products that support enterprise-wide consumption and decision-making.
• Support Data Mesh principles through domain-oriented data ownership and product-based data delivery.
• Champion modern Data Engineering principles and best practices across the Data & Analytics ecosystem.
• Build strong data foundations aligned with standards for data quality, observability, metadata management, lineage, security, and reusable data assets.
• Build trusted, governed, and reusable data assets though strong standards for data quality, observability, metadata management, lineage, security, and reusable data assets.
• Drive adoption of modern data platform capabilities and engineering best practices in partnership with Architecture and Data Engineering teams, ensuring enterprise data assets are scalable, reliable, governed, and optimized for analytics and AI.
• Champion effective utilization of Databricks and modern lakehouse technologies to support Data Products, Analytics, AI, and GenAI workloads.
• Provide technical leadership across Data, Analytics, AI, and Data Product initiatives, guiding opportunities from concept through delivery and value realization.
• Lead conceptual solution design activities, translating business requirements into scalable data and analytics capabilities.
• Partner with Enterprise Architecture and Corporate IT teams to shape solution strategies, architectural direction, platform adoption, and technology decisions.
• Evaluate solution options and trade-offs to balance business value, scalability, maintainability, and technical feasibility.
• Provide technical guidance and challenge to ensure solutions are scalable, secured, governed, reusable and aligned to intended business outcomes.
• Lead the identification, assessment, prioritization, and development of AI and GenAI opportunities across ADC.
• Partner with business stakeholders to define value-driven use cases, business outcomes, and success metrics.
• Evaluate opportunities based on strategic value, feasibility, adoption readiness, and alignment with legal, privacy, compliance, and cybersecurity requirements.
• Collaborate with Legal, Privacy, Cybersecurity, Data Science, Engineering, Architecture, and Delivery teams to support successful implementation of AI and GenAI initiatives.
• Promote responsible AI practices while monitoring adoption, business impact, and value realization of AI and GenAI solutions.
• Drive successful delivery of Data, Analytics, AI, and Data Product initiatives by partnering with Corporate IT, Architecture, Engineering, and business stakeholders to ensure commitments are delivered on time, within budget, and aligned to expected business outcomes.
• Lead intake, evaluation, and prioritization of Data, Analytics, AI, and GenAI initiatives.
• Facilitate investment trade-off discussions and portfolio decisions.
• Maintain visibility into initiative progress, risks, dependencies, and expected outcomes.
• Ensure investments, resources and delivery capacity remain focused on the highest-value opportunities.
• Provide portfolio recommendations and planning insights to business and Data & Analytics leadership.
• Champion a business-led data governance model that promotes ownership, accountability, and stewardship of critical data assets.
• Establish and support data ownership, stewardship, governance, and data quality practices across business domains.
• Promote adoption of metadata management, cataloging, governance, and compliance best practices to improve trust and usability of enterprise data.
• Advocate for trusted, governed, and AI-ready data assets that support strategic business objectives.

Benefits

• Employees can qualify for free medical coverage in our Health Investment Plan (HIP) PPO medical plan in the next calendar year.
• An excellent retirement savings plan with a high employer contribution
• Tuition reimbursement
• the Freedom 2 Save student debt program
• FreeU education benefit - an affordable and convenient path to getting a bachelor’s degree.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior