Experienced Analyst, 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 Experienced Analyst, Business Intelligence role supports the Procurement organization by delivering data, insights, and reporting that enable informed decision making and performance management across procurement operations. This role plays a key part in tracking procurement metrics including spend and fleet operations helping leaders identify trends, risks, and opportunities. This position offers strong exposure to enterprise-wide procurement activities and the opportunity to influence business outcomes through data driven insights.

·        BI solution delivery: Build, maintain, and enhance dashboards, reports, and self-service analytics solutions in Tableau and Power BI based on defined business requirements.

·        Business analysis: Analyze procurement and operational data, identify trends and exceptions, and translate findings into clear business insights and recommendations.

·        Collaboration: Partner with analytics process owners to ensure data accuracy, consistency, and alignment with business objectives.

·        Data preparation: Use approved data-preparation tools to extract, transform, reconcile, and prepare data for analysis and visualization while maintaining data integrity and resolving data quality issues.

·        Continuous improvement: Identify practical opportunities to simplify reporting, automate recurring work, improve usability, and increase adoption of trusted analytics products.

·        AI-assisted analytics: Use approved AI-assisted analytics capabilities for exploration and narrative development, validate outputs against trusted sources, and document assumptions and limitations.

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

·        2-4 years of relevant experience in business intelligence, data analytics, reporting, or a related discipline.

·        Hands-on experience developing dashboards and reports in Tableau or Power BI, including calculated fields or measures, filters, parameters, data relationships, and visualization best practices.

·        Ability to translate defined business questions into analytical approaches, identify meaningful patterns, and communicate findings clearly to business and technical audiences.

·        Experience contributing to BI projects or recurring reporting processes with general direction, while managing assigned tasks, timelines, quality, and issue escalation.

·        Strong analytical, problem-solving, documentation, communication, and collaboration skills.

·        Understanding data quality, access controls, privacy, security, and responsible use of approved AI tools.

·        Experience with cloud data platforms such as Databricks, Azure, AWS, or GCP.

·        Familiarity with Python, Tableau Prep, Alteryx, data warehousing, semantic models, or medallion architecture.

·        Exposure to procurement, supply chain, finance, or another data-intensive business function.

·        Experience supporting self-service analytics, dashboard adoption, user training, or reporting process automation.

·        Familiarity with Generative AI concepts, prompt construction, output validation, and responsible AI practices.