Manager, Business Intelligence

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at jnj.com.

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

The Manager, Business Intelligence is responsible for leading the delivery of trusted reporting, dashboards, and analytical insights that enable business decisions. This role partners with business and technology stakeholders to define KPI frameworks, prioritize the BI roadmap, and ensure scalable, governed solutions across tools and platforms (e.g., Databricks, Tableau, and Power BI). The ideal candidate blends strong people leadership with hands-on analytical expertise, ensuring the team delivers high-quality insights with consistent definitions and strong adoption.

·         Strategic leadership: Act as a top-level specialist to establish programs and innovative initiatives to advance effective Business Intelligence (BI) initiatives.

·         User enablement: Develop persona-based self-service analytics, dashboards, and reports aligned to business priorities and designed for adoption and actionability.

·         Strategic insight: Perform trend and competitive/market analysis and convert findings into actionable insights that continuously improve BI strategy.

·         Agile leadership: Operationalize AI-assisted analytics within the BI team by defining use cases, standard prompt patterns, and review/QA steps that improve speed and quality without compromising accuracy.

·         Accountability: Implement standards for visualization, QA, release management, and support (including monitoring, incident response, and refresh reliability).

·         Responsible AI: Ensure responsible and compliant use of AI in reporting and insights by partnering with Data Governance/Security to implement guardrails (access controls, approved tools, auditability) and by training the team on proper usage.

·         Accountability: Drive data governance adherence (security, access controls, lineage, and retention), partnering with Data Governance and Compliance.

·         Bachelor’s degree in Information Systems, Computer Science, Business Analytics, Statistics, Data Science, or a related field (or equivalent experience).

·         8+ years of experience in business intelligence/analytics roles with demonstrated delivery of dashboards and insights at scale.

·         Proficiency with Tableau and/or Power BI, including data modeling, visualization best practices, and stakeholder enablement.

·         Strong SQL skills and working knowledge of modern data platforms (e.g., Databricks) and data warehousing concepts.

·         Demonstrated ability to translate business questions into measurable KPIs, analytic approaches, and consumable insights.

·         Working knowledge of Source-to-Contract (S2C) and/or Procure-to-Pay (P2P) processes, including core objects and KPIs (e.g., supplier, contract, purchase order, invoice; spend, compliance, cycle time).

·         Ability to translate procurement stakeholder needs into governed KPI definitions, datasets, and dashboards that enable self-service and adoption.

·         Excellent communication and stakeholder management skills, with the ability to influence at multiple organizational levels.

·         Experience applying AI-assisted analytics to accelerate insight generation and stakeholder deliverables, with established review/approval steps to validate outputs and mitigate risk (privacy, bias, and hallucinations).

·         Experience building semantic layers and shared metric stores to support enterprise self-service analytics.

·         Familiarity with CI/CD for BI (deployment pipelines, version control, testing, and release automation).

·         Experience with data governance tooling and concepts (catalog, lineage, data quality monitoring).

·         Exposure to cloud platforms (Azure, AWS, or GCP) and lakehouse architectures.