Data Capability Engineer

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Own and extend the accuracy, completeness, and usability of the service management platform's data — so implementation teams and AI-driven capabilities can act on it directly, and so priority consumers like vulnerability and exposure management run on complete, trustworthy ground truth. Service mapping and asset data are the anchor domain and immediate priority; the durable mandate is data quality across an increasingly AI-centric ITSM platform, where automated systems act on data without a human to catch errors first.
A data-capability role, not a security role.

Core responsibilities — Anchor domain:
Service & asset data (immediate priority)

• Ensure existing service mapping is accurate and current across hosts, servers, and applications.

• Extend mapping coverage to data types not well covered today — certificates, websites, agents, and SaaS applications.

• Engage in the workflows that onboard new applications and capabilities into the CMDB so coverage keeps pace rather than drifting.

• Go deeper into discovery and software-asset tooling — Lansweeper, the software asset management system, and agent-based discovery — to raise inventory fidelity.

Core responsibilities — Broader mandate:
Platform & AI-consumption data quality

• Apply the same discipline to other high-value platform data — service catalog and metadata, ticket routing and assignment-group data, and the Dataverse structures underneath delivery capabilities such as the AskIT service chatbot.
• Raise data to the standard AI systems require: complete, disambiguated, and semantically clean, so intent classification, catalog matching, and automated routing act on trustworthy inputs rather than amplifying noise.

• Leverage the existing foundation (Dataverse schema, discovery tooling, search indexes already in place) rather than building net-new infrastructure.

• Make data consumable without re-verification - the test is whether an engineer or an automated agent can act on a record without re-checking it, and turn recurring data problems into repeatable quality practices.

What this role is not

• Not remediation coordination or change management

• Not a security function - it supplies the data; it does not own security decisions.

• Not a net-new platform build - leverages and improves the existing foundation.

Example Success measures

• Coverage: % of assets, certificates, websites, agents, and SaaS apps mapped to owner and service; extended over time to other platform data domains.

• Data confidence: high enough that implementation teams and AI capabilities don't require re-verification.

• Time-to-onboard a new application or capability into the CMDB.

• Reusability: improvements delivered as repeatable practices, not one-off fixes.

What You’ll Need:

Education:
Bachelor's degree in information systems, computer science, data management, or a related field — or equivalent practical experience. A candidate with a strong track record in CMDB, discovery, or data-quality work should not be screened out for lack of the exact degree.

Experience:
Five to eight years in IT data, configuration/asset management, or a data-engineering-adjacent role, including demonstrable ownership of a data domain (not just contributing to one). Enough experience to set the standard for how data quality is done, with the judgment to work independently under a Senior Manager's direction rather than needing task‑level supervision.

Required skills and knowledge
Anchor domain — asset & service data

• Hands‑on experience with CMDB and service mapping concepts (configuration items, relationships, service dependencies), including keeping mapping accurate as the environment changes.

• Working knowledge of…