Position Summary The Senior Enterprise Systems Analyst serves as the strategic bridge between business operations and enterprise technology. This role is responsible for ensuring software applications are designed, configured, and governed to support scalable business processes, high-quality data, enterprise reporting, and future AI initiatives. Rather than owning a single application, this position establishes enterprise standards that ensure systems across the organization work together to produce reliable, trusted, and actionable information. This role partners with business leaders, IT, software administrators, data engineering, and analytics teams to continuously improve how the organization captures, manages, integrates, and leverages information.

• Primary Responsibilities Enterprise System Governance
• Lead enterprise system design reviews before implementation
• Ensure new applications align with enterprise architecture standards
• Establish governance standards for application configuration
• Evaluate software requests to reduce unnecessary technology proliferation
• Maintain enterprise application inventory and technology roadmap
• Data Foundation & Information Architecture Support the organization's Strengthen Data Foundations initiative by improving how information is captured, stored, integrated, and governed.

Responsibilities include:

• Defining enterprise data standards
• Standardizing master data and value lists
• Designing scalable system configurations
• Eliminating duplicate or conflicting data
• Improving reporting readiness
• Supporting enterprise semantic models
• Ensuring systems are AI-ready through consistent, structured data
• Business Process Analysis
• Partner with business leaders to understand operational requirements
• Document business processes and future-state workflows
• Translate business needs into system requirements
• Identify automation opportunities
• Recommend technology improvements that reduce manual effort
• System Configuration & Standards Develop standards for:
• Naming conventions
• Value lists
• Metadata
• Security roles
• Organizational hierarchies
• Status definitions
• Workflow configuration
• Reference data
• Reporting structures Ensure every implementation supports enterprise reporting and downstream analytics.
• Reporting & Analytics Enablement Collaborate with Data Engineering and Business Intelligence teams to ensure enterprise systems:
• Produce trusted data
• Minimize manual transformations
• Support self-service reporting
• Improve dashboard adoption
• Reduce reporting complexity
• Integration & Enterprise Architecture Work across enterprise applications including:
• ERP
• Financial Systems
• HR Systems
• Project Management
• CRM
• Operational Systems
• Construction Management Platforms Responsibilities include:
• Mapping data flows
• Defining system ownership
• Identifying systems of record
• Supporting API integrations
• Reducing duplicate information
• AI & Digital Transformation Prepare enterprise systems for AI adoption by:
• Improving data quality
• Standardizing business definitions
• Supporting enterprise metadata
• Creating reusable data structures
• Reducing unstructured business processes
• Identifying opportunities for intelligent automation
• Leadership Responsibilities
• Lead cross-functional workshops
• Influence enterprise technology decisions
• Mentor junior analysts
• Develop enterprise standards
• Present recommendations to executive leadership
• Serve as trusted advisor to software owners
• Required Qualifications
• Bachelor's degree in Information Systems, Computer Science, Engineering, Business, or related field
• 7+ years supporting enterprise business applications
• Experience with enterprise software implementations
• Strong understanding of relational databases and SQL
• Experience with business process analysis
• Knowledge of data governance principles
• Experience working with enterprise reporting platforms
• Strong communication and stakeholder management skills
• Preferred Qualifications Experience with one or more:
• Microsoft Fabric
• Power Platform
• Power BI
• Azure
• ERP systems
• Procore
• Primavera P6
• Viewpoint Vista
• Microsoft Dynamics
• SAP
• Oracle
• Salesforce

ServiceNow Knowledge of:

• Enterprise Architecture
• Master Data Management
• Data Warehousing
• Kimball Modeling
• AI Governance
• Information Management
• Success Measures The successful candidate will help the organization achieve measurable improvements in:
• Enterprise data quality
• System standardization
• Reporting accuracy
• Self-service analytics adoption
• Reduction in duplicate applications
• Faster software implementations
• Reduced manual data transformation
• Improved process automation
• AI readiness
• Enterprise governance maturity