Job summary : the role will be supporting the in-flight initiatives, working with delivery and business partners as well as technical skills for building databricks foundations. See the details below. 3.Experience : 8to12Yrs 4.Required Skills : 5.Nice to have skills : 6.Technology : -Not Applicable 7.Shift : Day 8.Responsibilities : Core Job Responsibilities Strategic Business Partnership & Cross-Functional Alignment 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. Data Product Leadership & Design Thinking Establish, scale and mature the Data Product delivery model across Client Diabetes Care. Champion product-centric ways of working and enable adoption of Data Product principles across Client 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. Data Engineering & Platform Excellence 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. Technical Leadership, Solution Design & Architecture Alignment 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. AI & Generative AI Leadership Lead the identification, assessment, prioritization, and development of AI and GenAI opportunities across Client. 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. Portfolio Prioritization & Demand Management 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. Business-Led Data Governance & Stewardship 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.