About this role
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.
Please note that this role is available across multiple countries and may be posted under different requisition numbers to comply with local requirements. While you are welcome to apply to any or all of the postings, we recommend focusing on the specific country(s) that align with your preferred location(s):
Brazil R-107516, Colombia R-108718
Remember, whether you apply to one or all of these requisition numbers, your applications will be considered as a single submission.
Job Function:
Data Analytics & Computational Sciences
Job Sub Function:
Business Intelligence
Job Category:
Professional
All Job Posting Locations:
Bogotá, Distrito Capital, Colombia
Job Description:
We are recruiting for a Manager, Employee Listening, located in Sao Paulo, Brazil or Bogotá, Colombia.
HR Data & Intelligence sits at the heart of Johnson & Johnson’s HR Digital ecosystem, architecting the intelligence layer that shapes how the company understands, engages, and mobilizes its global workforce. This organization builds and operationalizes enterprise-scale data, analytics, and AI capabilities that do more than inform decisions—they reshape how HR plans, predicts, personalizes, and performs. By unifying data science, employee listening, knowledge management, and responsible AI, HR Data & Intelligence is transforming workforce signals into strategic advantage, ensuring HR is not only insight-led and future-ready, but a trusted steward of ethical, human-centered intelligence at scale.
The Employee Listening function is responsible for capturing, analyzing, and translating employee signals into actionable insights that inform HR strategy, product design, and leadership decision-making. The Manager, Employee Listenin g plays a critical part in both the execution of core annual employee surveys and the evolution of employee listening beyond periodic programs, helping shift listening toward a product‑oriented, always‑on capability. In doing so, the role integrates active feedback, passive signals, and contextual insights to better understand employee experience at scale.
Key Responsibilities:
Employee Listening Design & Delivery
- Strategy and Design : Contribute to the design and execution of a continuous, experience-based, and always-on employee listening strategy that extends beyond traditional surveys to deepen understanding of employee experience (e.g., pulse, lifecycle, crowdsourcing, passive signals, and external listening).
- Measurement : Develop survey measures that are valid, reliable, and actionable and aligned to organizational priorities.
- Survey Operations : Execute employee listening programs from program design through reporting, including methodology, content development, sampling, administration, analysis, and reporting.
- Program Management: Drive end-to-end program coordination for employee listening initiatives, including scope, timelines, resources, and stakeholder communication.
- AI-Enabled Listening : Build, test, and refine GenAI tools (e.g., Copilot agents, reusable prompts) to scale insight delivery, validating outputs against source data and following responsible AI practices
- Best Practices : Bring emerging trends and best practices into listening programs to strengthen decision-making.
Data Management and Analysis
- Manage Complex Data Sets: Prepare, validate, and maintain employee listening datasets to support accurate analysis and reporting.
- Quantitative and Qualitative Analyses : Analyze employee feedback and workforce data using quantitative and qualitative approaches to identify trends, key drivers, and root causes and generate actionable insights that inform decisions (e.g., reduce turnover, improve engagement).
Reporting and Visualization
- Reporting Quality and Compliance: Ensure reporting is accurate and meets enterprise, privacy, and legal requirements.
- Data Visualization : Build high-impact data visualizations and dashboards that help leaders interpret complex employee listening data and take action.
Consulting and Insight Delivery
- Trusted Advisor: Serve as a subject matter expert in employee listening, partnering with HR and business leaders to understand business objectives and recommend the right listening approach, program design, and content to inform decision-making.
- Insights and Storytelling: Present listening insights to HR and business stakeholders, including senior leaders, translating complex findings into clear narratives and recommendations.
- Leader Enablement and Action Planning : Develop toolkits, action-planning resources, and leader-facing materials that help stakeholders take action and strengthen follow-through on employee feedback.
- Internal and External Partnerships : Partner with technology, HR Data & Intelligence, and external vendors to deliver employee listening programs and integrate listening data with workforce, talent, and operational data.
Required Qualifications:
- Bachelor’s degree in Psychology, Organizational Behavior, Human Resources, Social Sciences, Data Science, or a related field.
- 5 years of experience in employee listening, people analytics, or organizational research roles
- Deep technical experience in survey methodology, including item design, psychometrics (e.g., factor analysis, reliability), construct/content validation, and sampling.
- Strong statistical skills across quantitative (e.g., regression, key driver analysis, segmentation) and qualitative (e.g., text analytics, thematic coding of open-ended comments) methods.
- Hands-on experience managing large, complex datasets.
- Advanced Excel skills; proficiency in statistical software (e.g., R, Python, SPSS); data visualization tools (e.g., Tableau, Visier); and survey platforms (e.g., Qualtrics, Glint, Perceptyx); and experience with Workday and other HR systems data.
- Excellent communication skills, with the ability to present complex insights to non-technical and business audiences.
- Proven project management experience leading large-scale initiatives and managing multiple priorities while maintaining quality.
- Attention to detail to ensure data accuracy, consistency, and process discipline
- Strong collaboration skills, with the ability to work effectively with internal and external partners, and on a highly interdependent team.
- Comfort working independently, solving problems and moving work forward with limited oversight.
- Ability to adapt quickly, navigate ambiguity, and learn in a fast-moving environment with evolving needs.
- Fluency in reading and writing English
Preferred Qualifications:
- Advanced degree in Industrial/Organizational Psychology, Organizational Behavior, Human Resources, Statistics, Data Analytics, Social Sciences, or a related field
- Familiarity with data privacy, confidentiality, and the ethical use of employee data.
- Experience evolving employee listening beyond periodic surveys toward, always-on experience based models.
- Familiarity with passive listening signals (e.g., text feedback, behavioral indicators, operational signals)
- Experience using AI or GenAI to enhance listening approaches
- Experience supporting global or matrixed organizations, multilingual survey needs, and diverse stakeholder groups.
Required Skills:
Qualtrics, Qualtrics Survey, R Analytics, R Programming, Survey Design
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, Workflow Analysis