Data Quality Analyst II

Data Quality Analyst II

Requirements

• Strong technical, analytical, problem-solving and storytelling skills
• Proven attention to detail, with ability to ‘dive deep’ into data issues to find root causes that lead to quality/process improvement
• Demonstrated ability to collaborate, listen and influence across organizational boundaries
• Demonstrated ability to document, communicate, and guide teams through operational and technical issues related to data management and data quality
• Positive, self-motivated, flexible, persistent, with good interpersonal skills
• Proficiency with SQL (required)
• Proficiency with data visualization tools like PowerBI, Tableau, etc. (required)
• Working knowledge of ticketing systems and of managing backlogs (ServiceNow)
• Understanding of Business Transactional Systems (such as Salesforce, Oracle EBS, Siebel CRM)
• Previous work experience in data quality space leveraging third-party reference data (such as Dun & Bradstreet, and Acxiom)
• Previous work experience conducting quality reviews comparing core (master) and reference data sets against transactional systems data
• Understanding of Go-to-Market customer installs base/asset management processes and best practices, inclusive of constraints, compliance, and associated downstream implications.

Responsibilities

• Monitor and execute processes for new data requests, changes, and deletions, ensuring accurate data entry and maintenance in relevant systems
• Perform internet research to validate addresses and utilize Microsoft Excel for data analysis and reporting purposes
• Utilize data quality tools and techniques to ensure data accuracy and appropriateness for intended business use cases
• Enhance data management and improve data quality outcomes by documenting, profiling, and analyzing organization-wide data
• Maximize the value of data assets by contributing to the development of data quality rules, metrics, and thresholds that support critical business processes
• Support the resolution of data anomalies through data profiling, validation checks, and root cause analysis
• Gain stakeholder buy-in for process improvements and issue-resolution efforts by preparing and presenting quality analysis findings and actionable recommendations
• Identify missing or incorrect data via defined processes, reports, or tools, and initiate appropriate corrective actions or escalations to drive resolution
• Contribute continuous improvement of data management processes by identifying patterns in data issues, sharing recommendations, supporting (and when appropriate, leading) the development of new processes, reports, or tools
• Serve as an ambassador for Enterprise Data by sharing knowledge and promoting best practices for data usage across teams
• Cultivate trust and build expertise in company data and systems through ongoing collaboration with enterprise Process Owners, Subject Matter Experts (SMEs), Analysts, and Functional Data Stewards
• Act as a peer-to-peer coach by mentoring and onboarding new team members to ensure smooth knowledge transfer and team readiness
• Actively partner with cross-functional stakeholders to understand business needs and provide subject matter expertise on core (master) data in both day-to-day operations and project contexts
• Take ownership of operational tasks and provide team support, including ensuring adequate out-of-office coverage as needed.

Preferred Qualifications

• Knowledge of MDM principles and workflows (preferred)
• Proficiency in Microsoft Office Suite (or similar tools such as Google Workspace) (preferred)
• Experience with R or Python (preferred)
• Exposure to Business Transactional Systems (e.g., Oracle EBS, Siebel CRM, Salesforce) (preferred)
• Bachelor’s degree in Business/Economics/Finance, Math/Statistics, MIS, or other computational field of study (preferred)
• Minimum 4 years of experience in Data Management and Governance position (preferred)