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Thomson Reuters

Legal, financial data, and media services

Lead Data Governance & Quality Analyst - Service & Operational Data

Data ManagementConfirmed live in the last 24 hours
Full-timeGdańsk, Poland

About the Job

Requirements

  • At least 5 years of experience in data governance, data quality, analytics, or related data management roles; experience in a lead capacity is strongly preferred, ideally with operational, IT service management, or telemetry datasets.
  • Demonstrated experience defining and implementing data quality controls, including profiling, rules, monitoring, scorecards, and issue workflows, and partnering with teams to operationalize them.
  • Strong knowledge of data governance concepts, including data ownership and stewardship, critical data elements, metadata, lineage, data lifecycle, and controls, and how they apply to event, ticketing, and telemetry data.
  • Advanced SQL skills, including analyzing data in relational warehouses or lakes; working with semi-structured data such as JSON or log-like structures is a plus.
  • Working knowledge of data pipelines and common failure modes, including APIs, ELT/ETL, streaming versus batch, and ability to partner effectively with data engineering.
  • Experience working cross-functionally with business partners and technical teams such as Service Management, Engineering, Architecture, Product, Compliance, and Security.
  • Strong documentation, facilitation, communication, and stakeholder management skills, and ability to drive outcomes without direct authority.
  • Comfort working hands-on with data profiling, writing SQL checks, documenting definitions, and running working sessions.

Responsibilities

  • Lead governance execution for Service & Operational data domains, including Incident, Problem, Change, Request, Observability/Telemetry, Availability, and SLA/SLO, ensuring consistent definitions, ownership, and controls.
  • Develop and maintain data quality standards, including profiling, rule design, thresholds, completeness, accuracy, and timeliness checks, and automated monitoring and alerting for priority datasets.
  • Define and maintain data product expectations and contracts covering schema, definitions, freshness, SLAs/SLOs, and usage guidance; partner with engineering to implement controls and alerts to ensure compliance.
  • Partner with Data Owners and Stewards to define critical data elements, business glossaries, and data product or service expectations, including incident categorization, assignment group, CI mapping, SLA clocks, and telemetry tags.
  • Create and manage data quality scorecards and reporting, tie issues to business impact, track progress against KPIs, and run a regular review cadence with owners and stewards to drive decisions and prioritization.
  • Run data issue management with ITSM-style rigor, including intake, triage, severity and priority definitions, root-cause analysis coordination, remediation tracking, and post-fix validation; prevent recurrence through upstream controls and process improvements.
  • Support metadata management, including lineage, definitions, classifications, retention, and usage documentation in data catalog tools.
  • Ensure compliance and responsible data use by applying privacy and security classifications such as PII, access controls, and audit-ready documentation.
  • Influence upstream processes, including data entry, standards, integrations, reconciliation logic, and product changes, to prevent defects and reduce rework through measures such as mandatory fields, controlled vocabularies, CI normalization, and tag standards.
  • Contribute to the governance operating model through standards, playbooks, training, and change management to increase adoption across teams.
  • Facilitate governance forums, including working sessions and steward councils, drive decisions on definitions, quality thresholds, and prioritization, and maintain decision logs and backlog transparency.
  • Partner with Service Management, SRE/Observability, Engineering, and Data & Analytics teams to align on definitions, controls, and overall plans.

Desired Qualifications

  • Familiarity with governance frameworks and best practices, such as DAMA/DMBOK concepts.
  • Experience with catalog or governance platform tools such as Alation or similar platforms.
  • Experience with workflow tools such as ADO and ServiceNow.
  • Experience with the ServiceNow data model, including Incident, Problem, Change, and CMDB, and/or observability or telemetry, including metrics, logs, traces, and entity or identity mapping concepts.
  • Experience defining metrics for service reliability and operations, such as MTTR, Change Failure Rate, Availability, and SLA attainment, and standardizing calculation logic.
  • Understanding of privacy and security practices, including PII concepts, data retention, and access governance.
  • Experience supporting AI/ML or BI environments where data trust is critical.

About the Company

Thomson Reuters

Legal, financial data, and media services

Thomson Reuters provides intelligent information and professional services for law, tax, finance, and media. It serves law firms, corporations, government agencies, and financial institutions with platforms like legal research (Westlaw), tax software (UltraTax CS), financial market data, and news services. These products are accessed through subscription-based platforms, ensuring ongoing updates and a steady revenue stream. The company also monetizes through advertising on media platforms and data analytics sales. It distinguishes itself by offering a broad, integrated suite of industry-specific tools combined with AI, cognitive computing, and machine learning to improve accuracy, efficiency, and predictive analytics in research and data insights. Its goal is to be a trusted partner that helps professionals make informed decisions by delivering reliable information and decision-ready tools while pursuing responsible, values-driven initiatives.

Company size
10,001+
Company stage
IPO
Headquarters
Toronto, Canada
Founded
1851

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