Senior Data Quality Analyst, Master Data, Procurement Services
Requisition ID # 164330
Job Category: Information Technology
Job Level: Individual Contributor
Business Unit: Engineering, Planning & Strategy
Work Type: Hybrid
Job Location: Oakland
Department Overview
The Procurement Organization includes a staff of more than two hundred sourcing managers, buyers and analysts. Our mission is to deliver cost effective and valued procurement services through strategic, diverse, and sustainable business solutions. Our work requires close integration with all lines of business, finance, and our suppliers.
The Procurement Excellence Center (PEC) is a strategic function dedicated to driving procurement transformation, operational efficiency, and value creation across the organization. Within the Procurement organization, the PEC establishes best practices, standardizes processes, and leverages advanced analytics and market intelligence to enable data-driven decision-making. The PEC collaborates with all Procurement teams to enhance capabilities, improve performance, and optimize costs. Key focus areas include market intelligence and analytics, digital procurement transformation, risk management, supplier relationship management, governance, and capability development.
Position Summary
As the Senior Data Quality Analyst for Master Data within PG&E’s Procurement Services organization, you will drive enterprise-level data quality strategies and operational excellence across procurement master data domains (e.g., vendor, material, contract, pricing). You will ensure that data assets are accurate, complete, and fit for purpose by defining and executing data quality rules, conducting validations and profiling, implementing monitoring and reporting frameworks, and driving corrective actions in collaboration with cross-functional stakeholders.
This role expands upon traditional master data stewardship to include robust data quality ownership, focusing on proactive governance, measurable health metrics, remediation frameworks, and continuous improvement of data quality across PG&E’s procurement systems.
This position is hybrid, working from your remote office and your assigned work headquarters.
PG&E is providing the salary range that can reasonably be expected for this position at the time of the job posting. This salary range is specific to the locality of the job. The actual salary paid to an individual will be based on multiple factors, including, but not limited to, internal equity, specific skills, education, licenses or certifications, experience, market value, and geographic location. The decision will be made on a case-by-case basis related to these factors. This job is also eligible to participate in PG&E’s discretionary incentive compensation programs.
Pay Range display:
Bay Area – $98,000 to $134,000
Key Responsibilities
Data Quality Definition & Implementation
Define, document, and maintain data quality rules, validation checks, and acceptance criteria for procurement of master data elements (e.g., Service Codes, Vendor IDs, contract terms, material attributes).
Develop and implement scalable data quality frameworks that integrate both preventative and detective controls.
Collaborate with business SMEs, data stewards, and IT partners to set thresholds, standards, and KPIs for data quality measurement.
Data Quality Monitoring & Reporting
Design and operationalize data quality dashboards and reports to monitor data health, trends, and compliance against standards.
Collect, analyze, and present data quality metrics and insights to leadership and stakeholders, identify patterns, risks, and opportunities for improvement.
Track and escalate data issues using structured issue tracking and remediation workflows.
Data Profiling & Root Cause Analysis
Perform regular data profiling, completeness checks, and anomaly detection to validate data quality against business rules and governance standards.
Conduct root cause analysis to identify systemic issues and propose corrective actions with process owners and technology teams.
Governance & Standards
Support and enforce data governance policies and master data standards across procurement systems, ensuring alignment to enterprise frameworks.
Participate in governance forums and working groups to formalize stewardship roles, responsibilities, and data quality accountability.
Continuous Improvement
Lead process improvement initiatives to eliminate data quality gaps and reduce manual intervention.
Identify opportunities for automation of quality checks and validation logic in collaboration with engineering and platform teams.
Stakeholder Engagement
Build strong relationships with procurement, supply chain, finance, and IT teams to drive data quality initiatives, change management, and shared ownership.
Provide coaching, best-practice guidance, and advocacy on data quality principles across the organization.
Background Qualifications
Minimum
Bachelor's degree in Computer Science, MIS, Business Analytics, or related field (or equivalent experience).
5+ years of experience in data quality, master data management (MDM), or data governance roles supporting enterprise data functions.
Strong understanding of data quality dimensions such as accuracy, completeness, consistency, validity, and timeliness.
Demonstrated experience writing and implementing data quality rules, validations, and thresholds.
Experience with data profiling, analytics, and quality reporting tools.
Desired
Knowledge of MDM platforms, data governance/quality tools, and automated monitoring frameworks (e.g., Collibra, Informatica, Talend, Great Expectations).
Familiarity with SQL and scripting languages to support data profiling and quality automation.
Experience working with ERP (e.g., SAP) and procurement systems (e.g., Ariba).
Proven success in cross-functional collaboration and influence within complex enterprise environments.
Measures of Success
Effective definition and operationalization of data quality rules and metrics covering key procurement master data domains.
Increased data quality scores over time (measured via dashboards and KPIs).
Strong stakeholder engagement resulting in timely remediation of data issues and decreased rework.
Continuous improvements to data governance processes and automation yield enhanced data trust and reduced manual effort.
#featuredjob