Data Architect Manager

Description

Job Summary: Data Architect Manager who will lead data architecture strategy, design, and governance for enterprise and federated data architecture at Abbott, driving data products and analytics. Key Highlights: 1. Lead the enterprise and federated data architecture strategy. 2. Promote the Data as a Product concept and enterprise-scale data governance. 3. Design data architectures for advanced analytics, AI, and GenAI. **Job Title** Data Architect Manager **About Abbott** Abbott is a global healthcare leader that creates innovative science to improve people’s health. We are always looking ahead, anticipating changes in medical science and technology. **Working at Abbott** At Abbott, you can do work that matters, grow and learn, take care of yourself and your family, be authentically you, and live a full life. You’ll have access to: * Professional development with an international company where you can build the career you dream of. * A company recognized as a best place to work in dozens of countries worldwide and named one of the world’s most admired companies by Fortune. * A company recognized as one of the best large workplaces, as well as a top workplace for diversity, working mothers, women executives, and women scientists. **Key Responsibilities** ================================= **Enterprise and Federated Data Architecture Leadership** -------------------------------------------------------------- * Define and govern the enterprise data architecture strategy supporting a domain-oriented, product-centric federated data model. * Establish architectural standards, guidelines, and interoperability patterns enabling domain autonomy while maintaining enterprise coherence. * Own the maintenance of reference architectures for data platforms, data products, integration, and information consumption for analytical and AI use cases. * Ensure data architectures are scalable, secure, resilient, and aligned with enterprise and technology roadmaps. * Design and deliver logical and physical data models that translate business processes into analytics-ready structures, enabling data products and efficient information consumption. **Data Products, Modeling, and Semantics** -------------------------------------------- * Lead architecture grounded in the **Data as a Product** concept, clearly defining ownership, contracts, service-level agreements (SLAs), and data product lifecycle standards. * Define and govern enterprise-wide semantic consistency, including canonical entities, shared dimensions, KPIs, and business metrics. * Translate business and analytical requirements into robust conceptual, logical, and physical data models. * Promote consumer-centric data designs that support analytics, operational processes, and automated system consumption. **Master Data Management (MDM) and Enterprise-Scale Data Governance** ---------------------------------------------------------------- * Design Master Data Management (MDM) and reference data architectures that balance domain ownership with enterprise consistency. * Define patterns for master records ("golden records"), hierarchies, and shared master data aligned to each domain. * Lead a federated data governance model covering ownership, administration, quality, lineage, metadata, access controls, and regulatory compliance. * Ensure data governance is embedded through architecture, standards, automation, and tooling—avoiding centralized bottlenecks. **Data and Data Product Observability** ------------------------------------------------ * Define architectural standards for data and data product observability within the federated ecosystem. * Ensure data products expose measurable indicators related to quality, freshness, completeness, availability, lineage, and usage. * Promote monitoring, alerting, and operational reliability practices that strengthen trust in analytics and AI consumption. * Drive observability as a key enabler for self-service analytics and Artificial Intelligence adoption. **Enabling Analytics, AI, and GenAI** ----------------------------------------- * Design data architectures supporting enterprise-scale advanced analytics, machine learning (ML), and Generative AI. * Design data product interfaces and models enabling reuse of features, embeddings, vector stores, and Retrieval-Augmented Generation (RAG) patterns. * Collaborate with Enterprise Architects and platform teams to ensure data products are AI-ready from inception. * Define and enforce data governance, quality, and security standards. * Ensure compliance with applicable regulatory requirements for data in the pharmaceutical industry. * Collaborate closely with privacy, security, and regulatory compliance teams. **Collaboration, Influence, and Capability Development** -------------------------------------------------------- * Serve as senior architectural advisor to domain, platform, and data governance leaders. * Mentor senior data architects and engineers on practices aligned with Data Mesh and product-centric models. * Work closely with Product Owners, analysts, and engineers to translate business needs into data solutions. * Represent the Data and Analytics Center of Excellence (CoE) in enterprise architecture forums, promoting alignment across domains and initiatives. * Influence strategic decisions through thought leadership, conceptual clarity, and technical credibility. **Required Experience and Capabilities** ======================================== * Extensive experience as a **Senior or Principal Data Architect** in large, complex enterprise environments. * Demonstrated experience implementing enterprise data architectures aligned with **Data Mesh** models or product-centric approaches. * Deep experience in: + Enterprise data modeling and semantics. + Master Data Management (MDM). + Data integration and harmonization patterns. + Federated data governance frameworks. * Strong hands-on experience in data modeling and harmonization. * Proven experience designing and operating data products with defined ownership, contracts, and observability. * Successful track record scaling data governance through standards, automation, and architectural guidance. * Deep knowledge of enterprise business domains such as Commercial, Marketing, Finance, Operations, or Supply Chain. * Solid understanding of data requirements for AI and GenAI, including features, embeddings, and RAG architectures. * Excellent stakeholder management and executive-level influence skills. **Preferred Experience and Technologies** ======================================== Practical experience building data architectures on cloud-native platforms, including: * **AWS** as the primary cloud platform. * **Databricks** as the enterprise data platform. * **dbt** for analytics engineering and data transformations. * Experience with data modeling tools (e.g., **Idera** or equivalents). * Familiarity with data observability tools (e.g., **Elementary** or similar). * Experience with data catalogs, metadata management, and lineage solutions. * Knowledge of PMO processes, SDLC/SLC methodologies, and architectural documentation standards. * Experience in pharmaceutical or life sciences environments is highly valued. **Travel Requirements** ======================= This role requires occasional international travel to support key business activities such as stakeholder meetings, workshops, and team events. **Why Join the Data and Analytics CoE (EPD)?** ====================================================== * Actively participate in EPD’s evolution toward an enterprise-scale **Data as a Product** model. * Influence how domains develop reliable, observable, and AI-ready data products. * Operate at a strategic level within a mature and innovative Data and Analytics Center of Excellence. * Leave a lasting impact on EPD’s analytics and Artificial Intelligence capabilities through high-impact data architecture. Apply Now Follow your professional aspirations with Abbott to access diverse opportunities with a company that helps you build your future and live your best life. Abbott is an equal opportunity employer committed to employee diversity. Connect with us at www.abbott.com, on Facebook at www.facebook.com/Abbott, and on Twitter @AbbottNews and @AbbottGlobal.