Senior Business Data Analyst (Manufacturing Domain)

Job Title: Senior Business Data Analyst (Manufacturing Domain)
Location: Easton, PA

Job Overview:

• Should have Manufacturing domain expertise.
• Proven track record delivering Data Warehousing, Data Lake, Master Data Management, Analytics, or Data Product initiatives.
• Experience leading data discovery and business process analysis engagements.

Must have skills:

• Minimum 7 years of experience as a Business Analyst.
• Analytics, Data Analysis & Interpretation (Strong).
• Manufacturing / Automation domain experience.

Roles & Responsibilities:

• Organize and facilitate Design Thinking and Discovery workshops with business stakeholders.
• Understand the client's business goals, technology landscape, product roadmap, organizational structure, and key stakeholders.
• Elicit, analyze, and document business requirements into functional and non-functional specifications.
• Break down problem statements and create clear logical and functional flows.
• Analyze data to draw business-relevant insights and create data visualizations using tools like Power BI.
• Maintain a prioritized backlog on the use cases agreed upon with stakeholders.
• Define and track acceptance criteria, critical success factors, and ROI for each use case.
• Identify areas for optimization and enhancement throughout the project lifecycle.
• Proactively engage stakeholders through workshops, POCs, and proposals to deliver additional business value.
• Engage with business teams to understand what data they create and consume Data sources and origins.
• How data supports business decisions Current manual data preparation and challenges.
• Act as a consultant and trusted advisor, guiding stakeholders on data product best practices and opportunities.
• Identify, define, and prioritize data products based on business value, enterprise reuse, and cross-functional impact.
• Document business, functional, and data requirements, including user stories and acceptance criteria.
• Work with Data Architects, Data Engineers, and business teams to translate business needs into scalable data solutions.
• Define data product ownership, stewardship, and governance requirements.
• Create and maintain a Data Product Catalog, including business definitions, use cases, and success metrics.
• Analyze business processes to identify opportunities for reporting, analytics, automation, AI, and machine learning enablement.
• Facilitate stakeholder alignment and prioritization across multiple business functions.
• Drive adoption of standardized, trusted, and reusable data products across the organization.
• Track business value realization, user adoption, and continuous improvement opportunities.
• Ensure data products support multiple teams and business processes while maintaining quality and governance standards.