Data & Analytics Lead

Join Amgen’s Mission of Serving Patients

At Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do. Since 1980, we’ve helped pioneer the world of biotech in our fight against the world’s toughest diseases. With our focus on four therapeutic areas –Oncology, Inflammation, General Medicine, and Rare Disease– we reach millions of patients each year. As a member of the Amgen team, you’ll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives.
Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you’ll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career.

What you will do

Let’s do this. Let’s change the world. We are seeking an individual who thrives in ambiguity, capable of driving data and analytics initiatives with precision and purpose. You will support the implementation of strategies, systems, and processes that enable data-driven decision-making across procurement and supply chain. Reporting to the Source-to-Contract (S2C) Technology Enablement Lead, your responsibilities will include designing the analytics strategy, building pipelines, integrating platforms, enabling visualization capabilities, leveraging GenAI tools, and delivering actionable insights that inform strategic sourcing and procurement decisions.

Roles & Responsibilities

Data & Analytics Strategy

• Develop and implement enhancements aligned with broader S2C strategic objectives and enterprise data strategy.

• Define and manage a data and analytics roadmap, prioritizing dashboards, AI/ML models, APIs, and data products.

• Track value delivery through KPIs such as cycle-time reduction, supplier risk mitigation, savings enablement, and user adoption.

Data Engineering & Integration

• Build and manage pipelines into data lakes/lakehouses (e.g., Databricks/Delta), integrating ERP, CLM, SRM, and external data sources.

• Code in SQL and Python for data modeling, cleansing, and transformations.

• Implement robust data quality, governance, lineage, and audit controls.

Visualization & Storytelling

• Deliver executive-ready dashboards and insights using tools such as Power BI, Tableau, or Looker.

• Establish visualization standards and KPIs to enable consistent decision-making.

• Convert complex analyses into clear, compelling narratives for senior stakeholders.

Advanced Analytics & GenAI

• Apply GenAI tools for procurement use cases, including contract intelligence, supplier summaries, and clause analysis.

• Build predictive and prescriptive models for demand forecasting, supplier risk, and cost optimization.

• Leverage ML frameworks for experimentation, feature management, and human-in-the-loop governance.

Procurement & Supply Chain Domain Leadership

• Partner with category managers to translate procurement and supply chain problems into data-driven use cases.

• Support savings tracking, supplier diversity, ESG reporting, and risk analysis with data insights.

• Improve supplier master data accuracy, classification, and taxonomy.

Governance & Compliance

• Ensure analytics pipelines comply with SOX, GxP, GDPR, CSRD, and internal audit requirements.

• Own audit documentation, lineage records, and inspection readiness.

• Implement access controls, data minimization, and privacy standards.

Stakeholder Engagement & Change Management

• Act as a liaison between business and technical stakeholders to translate requirements into scalable data solutions.

• Lead training, adoption, and enablement for self-service analytics capabilities.

• Manage vendor relationships and ensure SLAs are met for analytics platforms.

Team Leadership

• Mentor analysts, engineers, and BI developers on data engineering, visualization, and governance practices.

• Promote best practices in agile delivery, backlog management, and predictable outcomes.

Functional Skills

Must-Have Skills

• Data Engineering: Hands-on experience with Databricks/Delta Lakehouse, SQL, Python, PySpark, orchestration tools, and CI/CD.

• Visualization & Storytelling: Proficiency with Power BI/Tableau/Looker and ability to craft executive-level narratives.

• GenAI & Analytics: Exposure to GenAI/ML platforms and ability to apply them in procurement/supply chain contexts.

• Domain Knowledge: Strong understanding of procurement and supply chain processes, supplier master data, and compliance frameworks.

• Governance & Compliance: Knowledge of SOX, GxP, GDPR, and audit practices.

Good-to-Have Skills

• Technical Liaison Experience: Ability to bridge between technical and business stakeholders.

• Change Management: Familiarity with training and adoption practices for analytics and digital tools.

• Data Science & AI: Experience with ML experimentation, feature stores, and advanced analytics techniques.

Soft Skills

• Communication & Influence: Ability to simplify complex analytics for stakeholders across procurement, finance, IT, and executive leadership.

• Strategic Thinking: Ability to design scalable, future-proof data solutions.

• Collaboration: Strong cross-functional team collaboration skills, including mentorship and knowledge transfer.

• Adaptability: Comfort in dynamic environments with shifting priorities.

• Problem Solving: Structured approach to tackling technical and business problems.

• Attention to Detail: Precision in handling data quality, governance, and regulatory documentation.