Mgr BI

Job description

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. Job Function: Data Analytics & Computational Sciences Job Sub Function: Business Intelligence Job Category: Professional All Job Posting Locations: Pune, Maharashtra, India Job Description: Manager, Reporting and Analytics , ASPAC Supply Chain provides strategic leadership for MedTech reporting and analytics, ensuring business intelligence capabilities scale with organizational growth. This role encompasses reporting and analytics across Plan, Deliver and Customer service functions. This role sets the vision for KPI governance, data products, and self-service analytics, and leads managers and senior individual contributors to deliver measurable business impact. The ideal candidate is a strong supply chain leader with deep BI expertise across Databricks and modern visualization platforms (Tableau/Power BI), capable of aligning stakeholders, maturing operating models, and advancing analytics standards. Key Responsibilities Strategic leadership: Define the Reporting and Analytics strategy, operating model, and multi-quarter roadmap aligned to business priorities and data platform direction. People leadership: Lead and develop BI leaders within the team, building a high-performing team and healthy talent pipeline. Stakeholder engagement: Partner with the Plan BU’s , Deliver and Customer Service   organizations to establish enterprise KPI governance, standard metric definitions, and reporting hierarchies to ensure consistent measurement across functions. Business Partnership SC Analytics: Partner with the Plan BU’s , Deliver and Customer Service   organizations to deliver end user requests through a structured Demand Intake Mechanism. Evaluate the scope of work, value impact and resource availability to commit timelines and deliver the products / analytical tools / dashboards for end users Cross-functional collaboration: Partner with Data Management to deliver scalable, governed data products leveraging Databricks and other data platforms. Agile leadership: Drive adoption of self-service analytics through semantic models, enablement, and clear documentation, reducing dependency on ad hoc requests. Next Gen Technology leadership: Establish and enforce responsible AI governance for BI (policies, approval workflows, model/tool standards, validation and monitoring expectations) to ensure compliant, trustworthy AI-assisted insights at scale. Set the strategy for AI-enabled self-service and conversational analytics (natural language to governed metrics), ensuring alignment to the semantic layer, KPI governance, and adoption goals. Analytical excellence: Oversee the design standards and user experience of Tableau/Power BI solutions, conversational business intelligence, ensuring persona-based insights and consistent visual language. Accountability: Create performance management and service-level expectations for BI delivery (quality, timeliness, uptime, and stakeholder satisfaction) for Business management: Manage budget, vendor/partner relationships for outsourcing requests as required , and tool strategy as applicable; evaluate and implement capabilities to improve efficiency and governance. Qualifications Bachelor’s degree in information systems, Computer Science, Business Analytics, Statistics, or a related field (Master’s preferred). 10+ years of experience in business intelligence, analytics, and/or data engineering, including enterprise-scale BI delivery. 5+ years of leadership experience, including managing managers, Analysts  leading cross-functional initiatives with multiple stake holders , managing competing priorities and navigating ambiguous scenarios to arrive at concrete deliverables. Demonstrated Supply chain experience ( 5 years Plus )  in Plan ( IBP , Inventory Management ) , Deliver and Customer service . Plan and Deliver exposure is a must with strong understanding of SC KPI’s like MAPE, BIAS , OTIF -D , SLOB and Dock to Stock undefined Strong understanding of data platform patterns, data modelling, and governance, including experience with Databricks , SQL and Python undefined Expertise in Tableau and/or Power BI at an enterprise level (architecture, standards, performance, security, and adoption). undefined Proven ability to align executives and stakeholders to a shared measurement framework and to communicate complex insights clearly. undefined Proven ability to lead responsible adoption of AI-assisted analytics and data management (including Generative AI) by setting guardrails, governance, and validation standards that protect data and improve decision quality. Experience designing and implementing enterprise semantic layers (e.g., tabular models) and standardized KPI hierarchies. Experience with data quality frameworks (testing, monitoring, and SLAs) and analytics product management practices. Demonstrated AI and agentic model building for the business intelligence and insights Familiarity with privacy, regulatory, and security requirements impacting analytics (role-based access, row-level security, and auditing). Other Desirable Skills : Advanced Analytics in Supply chain , Mentorship / Developing Others, Inclusive Leadership, Performance Measurement, Project Integration Management and Tactical Planning. Required Skills: Preferred Skills: Advanced Analytics, Business Intelligence (BI), Cross-Functional Collaboration, Data Analysis, Data Governance, Data Privacy Standards, Data Quality, Performance Measurement, Process Improvements, Tactical Planning, Team Management, Technical Credibility, Workflow Analysis