Join NTT DATA as a CMDB Data Health & Quality Analyst and play a crucial role in ensuring the accuracy and integrity of our enterprise configuration data. This mid-level position involves analyzing data discrepancies, driving quality improvements, and collaborating with technical teams to maintain a high standard for our CMDB.

NTT DATA is a global leader in technology services, dedicated to fostering innovation and accelerating client success. We are committed to building an inclusive and forward-thinking organization where exceptional individuals can thrive and grow.

Key responsibilities include monitoring the ServiceNow CMDB Health Dashboard to identify and address anomalies in completeness, correctness, and compliance. You will investigate orphaned, stale, and duplicate Configuration Items (CIs), analyze root causes of health metric failures, and implement targeted data cleansing activities. Developing and maintaining analytics, KPIs, and reports to communicate data health trends to IT leadership is also a core function.

Further responsibilities involve managing CI data attestation processes and coordinating with CI Owners and Data Stewards for data verification. You will also control and maintain CI exclusion lists in ServiceNow, champion CSDM alignment, and assist in establishing best practices for CI naming conventions and data standards. Acting as a liaison between technical operations, asset management, and system administrators to validate data inputs from discovery tools will be essential.

We are looking for candidates with 3-5 years of professional experience in IT asset management, IT operations, or a dedicated data quality/analytics role. Essential tool expertise includes strong hands-on proficiency with ServiceNow, particularly navigating the CMDB Health Dashboard, CI Class Manager, and core ITSM modules.

Solid analytical and problem-solving abilities are required, with experience in reporting tools, building scorecards, and utilizing SQL or custom filters. A deep understanding of configuration management frameworks and data quality dimensions is necessary. Excellent cross-functional communication and stakeholder management skills are crucial for articulating data issues and remediation actions effectively to diverse audiences.