The Sr. Manager, Data Architect will lead the design, development, and implementation of Amgens data architecture strategy, ensuring data is accessible, reliable, and secure for critical business operations, analytics, and AI solutions. They will manage and guide a team of data architects, collaborating closely with multi-functional partners to develop data architecture and establish architectural standards across the enterprise. The Data Architect will provide thought leadership in data architecture, data modeling, data security, and data governance frameworks. They will be accountable for designing data architectures for strategic Data and AI initiatives. Define and implement data architecture strategy and roadmap, ensuring alignment with business and IT goals. Lead a team of data architects, providing mentorship, technical guidance, and career development opportunities. Work closely with data science, data engineering, and analytics teams to understand their data consumption and data processing needs and make data architecture recommendations to meet their needs. Engage with business, IT, and Data Strategy & Governance team to design efficient data flows: from data creation to how it flows across various systems, all the way to the points of consumption. Document these data flows using visual modeling tools. Articulate the data flows to various executives and partners and make recommendations on simplifying/optimizing the overall data architecture across Amgen s business functions. Develop cost estimates, resourcing plan, timeline, value proposition, and case for implementation of these recommendations. Present the case to partners to get their consensus. Design scalable, high-performance, and secure data architectures that support analytics, AI/ML, and operational workflows. Stay ahead of industry trends and innovations to drive best practices in data architecture and discuss those with partners. Establish enterprise-wide data modeling standards for structured, semi-structured, and unstructured data. Partner with Data Strategy & Governance and Engineering teams to implement metadata management and data lineage tracking to improve data discovery and quality. Collaborate with Data Strategy & Governance team on implementation of data governance policies to maintain data integrity, security, and compliance with regulations. Collaborate with information security team to establish and maintain data security and privacy controls. Collaborate with data stewards to manage data access controls and protect sensitive data. Develop and maintain documentation on data architecture, standard processes, and policies. Communicate complex data concepts to non-technical audiences effectively. What we expect of you We are all different, yet we all use our unique contributions to serve patients. Basic Qualifications: Doctorate degree and 2 years of Information Systems experience OR Master s degree and 8 to 10 years of Information Systems experience OR Bachelor s degree and 10 to 14 years of Information Systems experience OR Diploma and 14 to 18 years of Information Systems experience 4 years of managerial experience directly managing people and leadership experience leading teams, projects, or programs. Relevant experience in Pharma. Soft and technical skills: In-depth knowledge of Pharma processes with preferred specialization in a domain (e.g., R&D, Commercial, finance, Operations, etc.) 5+ years of experience in designing and implementing data architectures and data engineering. Proven leadership skills with a track record of managing and mentoring hard-working data architecture teams. Proven expertise in data architectures design for large organizations, data modeling, database design, and cloud platforms (AWS, Azure, GCP). Experience with big data technologies and modern ETL/ELT frameworks. Strong understanding of data governance, data security, and compliance standards. Experience managing multi-functional teams and enterprise-wide data initiatives. Preferred Qualifications: Certification in cloud data architectures (AWS, Google Cloud, or Azure). Experience with machine learning and AI-driven data architectures. Familiarity with DevOps, CI/CD, and infrastructure-as-code (Terraform, CloudFormation). Experience working with agile development methodologies such as Scaled Agile. Soft Skills: Excellent analytical and troubleshooting skills. Strong verbal and written communication skills Ability to work effectively with global, virtual teams High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals Strong presentation and public speaking skills.