Job Details
Location: Across United States
Salary: Not specified
Company: ApnaWorker
We are seeking a highly analytical Senior Data Analyst to support enterprise-wide technology risk, compliance, and tech debt remediation initiatives. This is a high-visibility role focused on transforming complex infrastructure and application data into actionable business insights for executive leadership. Key Skills Required: Advanced Excel (Expert Level), ServiceNow CMDB, Data Modeling & Analysis, Risk Analytics, Tech Debt Remediation, Data Governance, Power Query, Executive Reporting. Key Responsibilities: Build and maintain centralized datasets across applications, infrastructure, software inventory, and ownership mappings; analyze and reconcile data from CMDBs, vulnerability tools, software inventories, and enterprise systems; develop risk-based prioritization models for technology remediation initiatives; design advanced dashboards, reports, and executive scorecards; identify and resolve data quality issues across enterprise platforms; support technology risk reduction and modernization programs; deliver actionable insights to senior leadership and business stakeholders. Required Experience: Strong experience with ServiceNow CMDB; Advanced Excel skills including Pivot Tables, Power Query, and complex formulas; experience working with large-scale enterprise datasets; data modeling and interpretation experience beyond standard reporting; understanding of application, infrastructure, operating system, and software lifecycle management; experience supporting risk, compliance, cybersecurity, or tech debt programs. Preferred Skills: Power BI, Python, Microsoft Copilot, AI-powered analytics tools, Enterprise Data Integration, Risk & Compliance Analytics. What We're Looking For: Strong analytical and problem-solving mindset; ability to identify data gaps, inconsistencies, and root causes; experience translating technical findings into business recommendations; excellent communication and stakeholder management skills; ability to work independently in a fast-paced environment.