Senior Manager, Data & Analytics

Senior Manager, Data & Analytics

What you will do

Let’s do this. Let’s change the world. In this vital role, you will serve as the business engagement and technical delivery lead for prioritized Enterprise Data Strategy & Engineering (EDSE) initiatives. You will lead the strategy, delivery, and lifecycle of enterprise data products and AI-enabled data capabilities that make trusted data easier to discover, access, reuse, and apply across Amgen.

You will partner with Business Owners, EDSE Platform, Engineering, Governance, Architecture, Agile/PMO, and Amgen GCC Engineering teams to translate strategic priorities into scalable data, analytics, reporting, and AI-enabled solutions. You will shape roadmaps and delivery plans, manage dependencies, and deliver measurable business value.

The role will help advance EDSE’s FAIR data ambition by building reusable, governed data products and modernizing delivery through Databricks, AWS, Power BI, and other EDSE strategic platforms. You will identify and scale opportunities for agentic data engineering, AI-assisted development, automated quality and observability, and intelligent data operations—while maintaining enterprise standards for security, privacy, compliance, reliability, and cost.

Responsibilities

• Business engagement and product strategy

• Lead discovery with Business Owners; translate priorities into product visions, value cases, roadmaps, backlogs, and measurable success criteria.

• Maintain alignment on priorities, scope, investment, sequencing, risks, dependencies, and trade-offs.

• Communicate strategy, delivery progress, key decisions, and realized value to business and technical stakeholders.

• Technical delivery leadership & innovation

• Lead delivery of enterprise data products and analytics solutions using Databricks, AWS, Power BI, and other EDSE strategic platforms.

• Advance FAIR data principles by ensuring products are findable, accessible, interoperable, reusable, governed, and designed for trusted consumption across business domains.

• Define and scale innovative engineering patterns, including agentic data engineering, AI-assisted development, automated pipeline creation, metadata generation, data-quality monitoring, observability, and intelligent incident resolution.

• Partner with EDSE and Amgen GCC Engineering teams to turn emerging AI and data capabilities into production-ready, scalable services and products.

• Balance innovation with enterprise architecture, security, privacy, compliance, reliability, cost, and operational-support requirements.

• Value realization and lifecycle management

• Define and track adoption, operational, delivery, and business-value metrics for assigned initiatives.

• Lead post-launch adoption, support, enhancement prioritization, and lifecycle management.

• Promote reuse of EDSE platforms, shared data products, and engineering patterns to enable scalable enterprise delivery.

• What we expect of you

• We are all different, yet we all use our unique contributions to serve patients. The professional we seek is an individual with these qualifications.

Basic Qualifications:

• Doctorate degree and 2 years of experience in Data Engineering, Information Systems, Business, Engineering, Data & Analytics, or a related field

• OR

• Master’s degree and 6 years of experience in Data Engineering, Information Systems, Business, Engineering, Data & Analytics, or a related field

• OR

• Bachelor’s degree and 8 years of experience in Data Engineering, Information Systems, Business, Engineering, Data & Analytics, or a related field

• OR

• Associate’s degree and 10 years of experience in Data Engineering, Information Systems, Business, Engineering, Data & Analytics, or a related field

• OR

• High school diploma / GED and 12 years of experience in Data Engineering, Information Systems, Business, Engineering, Data & Analytics, or a related field

• In addition to meeting at least one of the above requirements, you must have a minimum of 2 years of experience directly managing people and/or leadership experience leading teams, projects, programs, or directing the allocation of resources. Your managerial experience may run concurrently with the required technical experience referenced above.

Required Qualifications:

• Experience delivering data, analytics, reporting, or digital solutions in the life sciences industry, working with large global teams

• Demonstrated experience delivering governed, reusable data products, such as curated datasets, domain data products, semantic models, data pipelines, or analytics products.

• Experience applying FAIR data principles or comparable practices for data discoverability, accessibility, interoperability, reuse, quality, ownership, and governance in life science industry.

• Demonstrated experience leading innovation in data engineering, analytics, AI, automation, or cloud platforms and converting pilots into scalable production capabilities.

• Strong stakeholder-management, communication, facilitation, and decision-making skills.

Preferred Qualifications:

• Experience with agentic data-engineering capabilities, including AI-assisted pipeline development, intelligent data-quality remediation, metadata and documentation generation, observability, and automated incident triage or resolution.

• Experience developing an enterprise data-product operating model, data marketplace, data catalog, domain ownership model, or reusable data-services ecosystem.

• Experience translating new AI and data capabilities into compliant, secure, production-grade solutions in a regulated life sciences environment.

• Experience with Agile or scaled