Data Analyst, Enterprise Data Governance Team
Intel
- Location
- US Arizona Phoenix
- Work model
- On-Site
- Level
- Mid
- H-1B history
- 1,112 approvals (FY2023)
- Posted
- Aug 13, 2026
Skills
About this role
Job Details
Job Description: Are you ready to play a pivotal role in transforming Intel's enterprise data ecosystem and enabling data-driven decision-making? As a Data Analyst on the Enterprise Data Governance Team, you will help improve Intel's business performance by applying data analysis, governance operations, process execution, and measurement practices to complex enterprise data challenges. In addition to domain analytics responsibilities, this role serves as a key execution partner to EDGT. The role supports the operationalization of enterprise data governance decisions, standards, controls, and processes across one or more data domains. The role is expected to engage across multiple enterprise data domains over time to support consistent governance execution, adoption, and maturity. This position acts as a bridge between business stakeholders, EDGT, domain owners, data stewards, architecture teams, platform teams, and development teams. The role translates governance decisions into executable actions, supports fit-gap and readiness assessments, manages governance work visibility, and helps ensure standards are adopted and sustained across the enterprise. The role will also support Governance Operations, Platform, and JIRA responsibilities within the proposed EDGT capability-based model. This includes EDGT operations, JIRA/work tracking, tooling roadmap coordination, capacity visibility, operating rhythm support, templates, documentation, and process orchestration. A critical part of this role is the development and ongoing measurement of data governance metrics that help Intel track progress on its enterprise data governance journey during IAO and beyond. The successful candidate will help define, maintain, and improve governance KPIs, scorecards, maturity indicators, adoption measures, and value-realization metrics that show how governance is progressing across domains, where gaps remain, and where leadership attention is needed. Key responsibilities include: Support execution and adoption of Enterprise-approved data governance standards, guidelines, controls, procedures, and decision frameworks. Support Governance Operations, Platform, and JIRA activities, including work tracking, backlog visibility, status reporting, dependency tracking, capacity views, templates, and operating rhythm support. Develop, maintain, and continuously improve data governance metrics, KPI frameworks, dashboards, scorecards, and maturity measures. Track governance progress during IAO and ongoing enterprise transformation, including adoption of standards, data quality outcomes, stewardship engagement, metadata maturity, issue remediation, and governance value realization. Provide executive-ready reporting and insights that show governance progress, risks, trends, gaps, and recommended actions. Analyze complex datasets to identify trends, risks, gaps, and opportunities that drive business insights and operational improvements. Gather business and technical requirements and translate them into actionable data specifications, governance requirements, and execution plans. Perform fit-gap analyses, readiness assessments, and risk assessments of data systems, processes, and domains to evaluate alignment with EDGT-approved governance standards. Serve as the day-to-day bridge between EDGT, domains, architecture, tooling, stewardship, and execution teams. Partner with domain, architecture, platform, and business teams to translate governance decisions into sustained practices and measurable outcomes.
Qualifications
Minimum Qualifications Bachelor's degree in a related field such as data science, information systems, supply chain, material science, industrial engineering, business analytics, or a related discipline. 3+ years of relevant experience in data governance, data quality, data processes, business analysis, operations, and technology-enabled process improvement. Experience analyzing complex datasets and translating insights into