Back
Specialized manufacturing data domain and seniority reduce applicant density despite strong employer brand.
Manufacturing and regulated life-sciences domain expertise makes skills less transferable across industries.
Explicit 8–13 years, domain expertise, and specific platform/certification preferences enforce strict filtering.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Translate manufacturing business needs into clear product and system requirements including epics, features, user stories, acceptance criteria, and test scenarios.
Lead workshops with manufacturing SMEs and stakeholders to document operational processes, data requirements, and support Agile product delivery activities like backlog prioritization and PI planning.
Collaborate closely with data engineers, architects, UX/UI teams, and QA to ensure solutions meet business, functional, quality, and compliance standards including support for testing, defect management, and user acceptance testing.
Bachelor’s or Master’s degree in Computer Science, IT, Engineering, Business, Data, or related field.
8–13 years of relevant experience in business systems analysis, product analysis, or requirements engineering.
Proven skills in manufacturing domain knowledge translating to functional and data requirements.
Experience with Agile, SAFe, Scrum, and tools like Jira and Confluence for managing requirements and delivery.
Experienced in bridging manufacturing subject matter expertise and technology teams within regulated or manufacturing environments.
Skilled in detailed requirements capture including data, analytics, reporting, KPIs, and process flows.
Comfortable working in Agile and Scaled Agile environments coordinating across global, cross-functional stakeholders.