Data Steward
Career GuideKey Responsibilities
- Define and maintain common definitions for important data
- Set data quality rules and track data quality results
- Review and correct data issues with business and technical teams
- Maintain documentation for data fields and data sources
- Support data access requests using agreed rules and approvals
- Help ensure data handling follows internal policies and external regulations
- Assist with data change reviews for new systems and process updates
- Promote good data practices through training and support
Top Skills for Success
Attention to Detail
Stakeholder Communication
Process Improvement
Problem Solving
Data Quality Management
Data Standards
Data Definitions
Metadata Management
Data Governance
SQL
Data Privacy
Risk Awareness
Career Progression
Can Lead To
Senior Data Steward
Data Governance Analyst
Data Quality Analyst
Master Data Specialist
Transition Opportunities
Data Governance Manager
Data Product Manager
Analytics Manager
Data Compliance Manager
Data Operations Lead
Common Skill Gaps
Often Missing Skills
Metadata ManagementData LineageSQLData Quality MonitoringData Access ControlsData Catalog ToolsChange Management
Development SuggestionsBuild confidence in SQL and basic data investigation. Practice writing clear data definitions and documenting data sources. Learn one data catalog tool and one data quality tool used in your target industry. Partner with security and compliance teams to understand access rules and privacy expectations.
Salary & Demand
Median Salary Range
Entry LevelUSD 60,000 to 85,000
Mid LevelUSD 85,000 to 115,000
Senior LevelUSD 115,000 to 145,000
Growth Trend
Demand is steady to growing, driven by analytics adoption, regulatory pressure, and company focus on trustworthy reporting. Hiring is strongest in regulated and data-heavy industries.Companies Hiring
Major Employers
JPMorgan ChaseBank of AmericaWells FargoUnitedHealth GroupCVS HealthKaiser PermanenteAmazonMicrosoftIBMAccentureDeloittePfizer
Industry Sectors
Financial ServicesHealthcareInsuranceRetailTechnologyManufacturingPharmaceuticalsGovernmentConsulting
Recommended Next Steps
1
Create a sample data dictionary for a familiar dataset with clear definitions and owners2
Practice identifying data quality issues and proposing specific rules to prevent them3
Strengthen SQL skills for checking data consistency and tracing issues to a source4
Learn your industry’s privacy and retention requirements and summarize how they affect daily work5
Add a portfolio entry that shows documentation, issue tracking, and measurable quality improvements6
Network with data owners and analysts to understand how trusted data impacts decisions