Data Process Lead

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.

• Serve as the data subject matter expert for Global Services and SCS initiatives, supporting the Sr. Manager, Data Solutions in translating business needs into scalable data, reporting, analytics, automation, and AI capabilities.
• Assess impacts and risk of business, data, and reporting requirements based on project or strategic decisions, and provide potential solutions and mitigation plans to reduce impact.

• Design, build, and optimize data pipelines to ingest, transform, and integrate data from various sources and drive the end-to-end delivery of reporting and analytics or data product solutions within Global Services.
• Identify opportunities to use data, automation, analytics, Generative AI, and agentic capabilities to simplify data-intensive processes, improve quality, reduce manual effort, accelerate insight generation, and enhance employee and customer experiences.
• Responsible for building an inventory of current data assets, reports, and dashboards, and provide recommendations of future optimal solutions based on business requirements and capabilities within new technology implementations.
• Drive the build of data models within downstream systems, ensuring seamless historical and future reporting capabilities.
• Ensure existing data assets operate seamlessly with the implementation of new technologies and digital solutions.
• Design and implement scalable and efficient data integration architectures that meet business requirements. Ensure data integrity, quality, scalability, and security throughout the pipeline.

• Demonstrate influencing skills and credibility.
• Onboard and train new peers, as required
• Serve as a senior member of the team and continuously support and advise other team members

• Exhibit an unbiased and integrated approach towards business partnering.
• Execute global Strategy & Solutions in line with taxonomy.

• Generate ideas, foster and implement a continuous improvement mindset, identifying and pursuing data and process efficiency opportunities.
• Identify opportunities to simplify processes through intelligent automation, predictive insights, Generative AI, and emerging AI capabilities.
• Execute improvements, generating ideas and implementing in line with global standards.

• Bachelor's degree or equivalent in a related field (e.g., Computer Science, Information Systems, Data Science, Business Analytics, or a related field) is required. Advanced degree preferred.

• 6-8 years of experience in data, reporting and analytics development, preferably in a global or multinational organization.
• Strong knowledge of data governance frameworks, data quality management, and data integration methodologies.
• Experience identifying and translating business challenges into data, analytics, automation, or AI-enabled solutions.
• Experience working with structured and unstructured data, including documents, knowledge content, metadata, and API-based data sources.
• Experience defining technical and data-quality acceptance criteria and validating that data is fit for its intended analytical or AI use.
• Proficiency in data analysis and visualization tools (e.g., SQL, Tableau, Python, etc.) is highly desirable.

• Experience working collaboratively with cross-functional partners and across organizational boundaries.  
• Proven ability to communicate and work effectively across teams to ensure successful development and launches.

• A proactive and results-oriented mindset, with the ability to prioritize tasks in a fast-paced environment.
• Proven ability to operate independently, manage ambiguity, and coordinate delivery across business, data, technology, architecture, risk, and governance stakeholders.
• Flexibility and adaptability to thrive in a multifaceted environment.

• Data Strategy
• Data Visualization
• Data Literacy & AI Literacy
• AI Enablement and Generative AI concepts
• Data Engineering (ETL, Data Warehousing, Data Lakes, Lakehouse)
• SQL
• Agile Processes (Scrum, Kanban)
• DevOps / CICD / MLOps
• Data modeling