Data & Analytics Lead

At Amgen, if you feel like youre part of something bigger, its because you are. Our shared missionto serve patients living with serious illnessesdrives all that we do. What you will do 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.

Digital Product Ownership

• Own product vision, OKRs, and roadmap aligned to S2C/S2P and enterprise data strategy.
• Maintain a single, prioritized backlog across pipelines, semantic models, APIs, dashboards, and GenAI.
• Run discovery and define success metrics (adoption, cycle time, savings, SLOs, DQ).
• Treat data as a product: accountable owners, SLAs, data contracts, versioning, and deprecation plans.
• Govern releases: feature flags, controlled changes, release notes, and user training.
• Manage vendors and TCO; negotiate SLAs; track license utilization and value realization.

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 .

Basic Qualifications:

• Btech/ MBA/ PHD
• Minimum of years of relevant business and functional experience