Opportunities in India

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Capability Engineer based in India. This role is responsible for improving the accuracy, completeness, and usability of critical IT service management data. You will own and extend service mapping and asset data so implementation teams and AI-enabled capabilities can rely on trustworthy information. The position combines CMDB expertise, data quality, discovery tooling, and structured data management in an increasingly AI-centric environment. You will expand data coverage across assets, applications, certificates, websites, agents, and SaaS platforms. Beyond the core service and asset domain, you will help raise the quality of service catalog, metadata, routing, and other platform data. Success means creating reliable, reusable data practices that allow both people and automated systems to act confidently without repeated verification.

Own the accuracy, completeness, and usability of service management platform data, with service mapping and asset information as the immediate priority. Ensure existing service mappings remain accurate and current across hosts, servers, applications, and their associated relationships and dependencies. Expand service and asset mapping coverage to additional data types, including certificates, websites, agents, and SaaS applications. Participate in application and capability onboarding workflows to ensure CMDB coverage grows consistently and does not deteriorate over time. Work extensively with discovery and software asset management tooling, including Lansweeper, agent-based discovery, and related inventory systems, to improve data fidelity. Apply strong data-quality practices across broader platform domains such as service catalogs, metadata, ticket routing, assignment-group data, and Dataverse structures. Prepare platform data for AI consumption by ensuring information is complete, disambiguated, normalized, and semantically clean. Support reliable intent classification, catalog matching, automated routing, and other AI-enabled capabilities by providing trustworthy underlying data. Leverage existing Dataverse schemas, discovery tooling, search indexes, and platform capabilities rather than creating unnecessary new infrastructure. Query, profile, validate, normalize, and correct data at scale while maintaining strong standards for completeness and accuracy. Embed data quality into existing operational and onboarding workflows, turning recurring issues into repeatable and sustainable practices. Establish data that can be consumed confidently by implementation teams and automated agents without requiring manual re-verification. Monitor and improve key measures such as asset and service coverage, data confidence, onboarding time, and reuse of data-quality practices. Communicate data issues, root causes, business impact, and recommended improvements clearly to technical and non-technical stakeholders. Operate as a data capability specialist rather than a security owner, remediation coordinator, or net-new platform builder, while supporting functions that depend on reliable data. Requirements: Bachelor’s degree in information systems, computer science, data management, or a related field, or equivalent practical experience. Strong hands-on experience in CMDB, discovery, or data-quality work may substitute for the exact degree. 5–8 years of experience in IT data, configuration management, asset management, data engineering, or a closely related discipline. Demonstrated ownership of a data domain, with the ability to define and maintain standards for data quality independently. Strong hands-on understanding of CMDB and service mapping concepts , including configuration items, relationships, service dependencies, and maintaining mappings as environments evolve. Practical experience with discovery and software asset management technologies, including Lansweeper, agent-based discovery, and software asset management systems . Understanding of asset types such as certificates, websites, agents, SaaS applications, servers, hosts, and applications. Strong data-quality fundamentals, including profiling, deduplication, normalization, validation, and measurement of data completeness and accuracy. Experience querying and shaping data within a structured platform such as Microsoft Dataverse or a comparable relational or low-code data platform. Strong query capabilities that enable independent investigation, validation, and correction of data at scale. Understanding of the characteristics that make data suitable for AI consumption, including completeness, disambiguation, consistency, and clean semantics. Familiarity with how high-quality data supports AI use cases such as intent classification, catalog matching, and automated routing; deep machine-learning expertise is not required. Ability to embed quality controls into existing workflows and transform recurring data issues into repeatable operational practices. Strong communication skills, with the ability to explain data problems and their business impact to both technical teams and non-technical stakeholders. Ability to work independently under senior leadership direction without requiring task-level supervision. Experience within a Microsoft Power Platform environment, including technologies such as Power Automate or Azure AI Search, is an advantage. Exposure to vulnerability or exposure management as a consumer of asset data is beneficial, particularly an understanding of data requirements without owning security decisions. Familiarity with ITIL and/or data-management certifications such as DAMA/CDMP is an advantage. Benefits: Permanent, full-time employment opportunity based in Chennai, India . Opportunity to work at the intersection of IT service management, data quality, automation, and AI-enabled capabilities. Ownership of a critical data domain with direct impact on implementation teams and automated IT processes. Exposure to CMDB, service mapping, discovery, software asset management, Dataverse, and enterprise search technologies. Opportunity to establish scalable, repeatable data-quality practices rather than focusing solely on one-off data fixes. Collaboration with technical and business stakeholders across an evolving IT service management environment. Opportunity to contribute to AI-ready data capabilities without requiring a deep machine-learning background. Professional growth through ownership of a strategic data capability and exposure to modern enterprise technology. Compensation and benefits are provided in accordance with the applicable employment terms and company policies.