Senior IT Manager, Global Data and Analytics

Abbott Laboratories seeks a Senior IT Manager, Global Data and Analytics to lead enterprise data strategy across its biotechnology and pharmaceutical businesses. In this role, you will own the vision, roadmap, and execution of global data platforms, overseeing data engineering, BI, and analytics teams that power critical scientific, commercial, and operational decisions. Partnering with leaders across R&D, diagnostics, and commercial functions, you will translate complex business needs into scalable, secure, and compliant data solutions. You will champion data governance, quality, and advanced analytics adoption, ensuring alignment with regulatory standards while fostering an inclusive, growth-oriented, and innovative culture.

Responsibilities

• Lead global data and analytics strategy to support Abbott's biotechnology and pharmaceutical operations
• Oversee design, delivery, and governance of enterprise data platforms and analytics solutions
• Partner with business and scientific leaders to translate needs into scalable data products and dashboards
• Manage data engineering, BI, and analytics teams; mentor and develop technical talent
• Establish data quality, security, and compliance standards across regions
• Drive adoption of advanced analytics, including AI/ML, to improve decision-making and patient outcomes
• Collaborate with IT, R&D, and commercial teams on cross-functional initiatives
• Manage vendor relationships, budgets, and project portfolios
• Ensure solutions comply with healthcare, privacy, and regulatory requirements (e.g., HIPAA, Gx
• P)
• Continuously improve processes, tools, and architectures to enhance performance and reliability

Required Skills

• Data warehousing and data lake architecture (e.g., Snowflake, Redshift, Big
• Query, Azure Synapse)
• SQL and relational database design
• Cloud platforms (AWS, Azure, or GCP) for data and analytics workloads
• ETL/ELT and data integration tools (e.g., Informatica, Talend, dbt)
• Business intelligence and visualization tools (e.g., Power BI, Tableau, Qlik)
• Data governance, data quality, and master data management
• Advanced analytics and machine learning concepts and tooling (e.g., Python, R, Spark)
• Information security, privacy, and regulatory compliance in healthcare/life sciences
• IT project and portfolio management, including Agile practices
• People leadership, stakeholder management, and cross-functional collaboration