Data Integrity Specialist
Career GuideKey Responsibilities
- Monitor data quality and flag unusual changes or errors
- Investigate data issues and identify root causes
- Clean and correct data using approved processes
- Define data quality rules and validation checks
- Document data definitions and standard data entry practices
- Coordinate issue resolution with business teams and technical teams
- Track data quality metrics and report progress over time
- Support audits and compliance requests related to data accuracy
- Improve processes to prevent recurring data problems
- Test data changes after system updates or new integrations
Top Skills for Success
Attention to Detail
Problem Solving
Stakeholder Communication
Process Improvement
Data Quality Management
Data Validation
Root Cause Analysis
SQL
Data Profiling
Data Governance
Master Data Management
Metadata Management
Career Progression
Can Lead To
Data Quality Analyst
Data Governance Analyst
Master Data Specialist
Business Intelligence Analyst
Transition Opportunities
Data Governance Manager
Data Quality Lead
Data Steward
Analytics Engineer
Data Operations Manager
Common Skill Gaps
Often Missing Skills
SQLData Quality MetricsData LineageData GovernanceData Catalog ToolsIssue Tracking PracticesChange Management
Development SuggestionsBuild comfort with querying and basic data investigation, then practice designing clear data quality rules and tracking outcomes. Ask to own a recurring data quality dashboard and a small set of priority data issues from intake through resolution.
Salary & Demand
Median Salary Range
Entry LevelUSD 55,000 to 75,000
Mid LevelUSD 75,000 to 100,000
Senior LevelUSD 100,000 to 135,000
Growth Trend
Steady growth. Demand is supported by increased reporting needs, more connected systems, and higher expectations for reliable analytics and compliance.Companies Hiring
Major Employers
UnitedHealth GroupKaiser PermanenteJPMorgan ChaseBank of AmericaWells FargoAmazonWalmartTargetSalesforceAccentureDeloitteIBM
Industry Sectors
HealthcareFinancial ServicesRetailTechnologyInsuranceManufacturingTelecommunicationsGovernmentConsulting
Recommended Next Steps
1
Create a portfolio example showing how you identified a data issue, measured impact, and prevented recurrence2
Strengthen SQL skills using real tables and realistic data problems3
Learn how your organization defines key fields and align to a shared data dictionary4
Set up a simple data quality scorecard with accuracy, completeness, and timeliness measures5
Partner with system owners to add validation at the point of entry and during data transfers6
Get familiar with your company’s governance process and propose one improvement to reduce recurring errors