Lead Data Governance & Quality Analyst
Thomson ReutersRemotePosted 7 April 2026
Job Description
Job Requisition: Lead Data Governance & Quality Analyst – Service & Operational Data
Location: Bangalore (Hybrid); collaborate with AMERS/EMEA/APAC stakeholders as needed.
Job Type: Full-time; Lead-level (hands-on Individual Contributor)
We're hiring a Lead Data Governance & Quality Analyst to strengthen how we define, manage, and trust enterprise Service & Operational data across platforms such as ServiceNow, Datadog, and other IT-related systems. In this role, you'll own governance execution and data quality practices for core Service & Operational domains (e.g., IT Service Management (Incident, Problem, Change, Asset, CMDB, Request, Knowledge, SLAs/SLOs), observability telemetry (metrics, logs, events, synthetics, RUM). Where end-to-end service and operational metrics span multiple systems, you’ll partner partner with Customer Experience and Engineering teams (e.g., Salesforce, Azure DevOps) to align cross-domain definitions and quality requirements – driving outcomes through collaboration with business owners, data stewards, product teams, and engineering to ensure data is well-defined, measurable, compliant, and fit for purpose.
You'll translate policy into action by establishing clear data definitions, ownership, and measurable controls – implementing data quality rules, monitoring, issue management workflows, and governance operating rhythms that improve decision-making, reduce risk, and enable scalable analytics and AI.
About the Role
As our Lead Data Governance & Quality Analyst , you will:
Lead governance execution for Service & Operational data domains (e.g., Incident/Problem/Change/Request, Observability/Telemetry, Availability/SLA/SLO), ensuring consistent definitions, ownership, and controls.
Develop and maintain data quality (DQ) standards : profiling, rule design, thresholds, completeness/accuracy/timeliness checks, and automated monitoring/alerting for priority datasets.
Define and maintain data product expectations / contracts (schema, definitions, freshness, SLAs/SLOs, usage guidance) and partner with engineering to implement controls and alerts to ensure compliance.
Partner with Data Owners and Stewards to define critical data elements (CDEs), business glossaries, and data product/service expectations (e.g., incident categorization, assignment group, CI mapping, SLA clocks, telemetry tags).
Create and manage DQ scorecards and reporting , tying issues to business impact and tracking progress against KPIs; run a regular review cadence with owners/stewards to drive decisions and prioritization.
Run data issue management with ITSM-style rigor: intake, triage, severity/priority definitions, root-cause analysis coordination, remediation tracking, and post-fix validation; prevent recurrence via upstream controls and process improvements.
Support metadata management : lineage, definitions, classifications, retention, and usage documentation in data catalog tools.
Ensure compliance and responsible data use by applying privacy/security classifications (e.g., PII), access controls, and audit-ready documentation.
Influence upstream processes (data entry, standards, integrations, reconciliation logic, product changes) to prevent defects and reduce rework (e.g., mandatory fields, controlled vocabularies, CI normalization, tag standards).
Contribute to governance operating model : standards, playbooks, training, and change management to increase adoption across teams.
Facilitate governance forums (working sessions, steward councils) and drive decisions on definitions, quality thresholds, and prioritization; maintain decision logs and backlog transparency.
Partner closely with Service Management, SRE/Observability, Engineering, Data & Analytics teams to align on definitions, controls, and overall plans.
About you:
To be our Lead Data Governance & Quality Analyst , you will likely have:
5 years in data governance, data quality, analytics, or related data management roles; experience in a lead c ... (truncated, view full listing at source)
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