Role Scope

The Data Steward is an individual contributor role responsible for executing core data stewardship activities that ensure the accuracy, integrity, and governance of enterprise data assets.

The Data Steward:

• Manages end-to-end lineage monitoring
• Maintains high-quality metadata
• Enforces policy and control compliance
• Supports UAT (User Acceptance Testing) for database changes and product distribution
• Performs detailed data validation and vendor data reviews
• Works closely with Technology and Data Operations teams to resolve issues and maintain consistent data standards across systems

Additionally, the Data Steward contributes to process improvement by:

• Driving standardization initiatives
• Enhancing documentation practices
• Supporting automation and AI-enabled capabilities
• Improving data quality
• Reducing manual effort
• Strengthening operational efficiency and vendor management

What You'll Do (Key Responsibilities)

Operational Delivery

• Perform data validation checks, lineage tracking, and metadata updates to maintain data quality, integrity, and traceability.
• Execute data ingestion, validation, and integration activities in alignment with governance and control standards.
• Ensure consistent adherence to enterprise data policies and governance frameworks.
• Execute defined controls and compliance requirements to safeguard data integrity and lineage.
• Support vendor data reviews and onboarding through data quality assessments, validation checks, and issue resolution.
• Maintain data standardization, stewardship documentation, and process artifacts to ensure accuracy and consistency.
• Execute medium-complexity stewardship and validation tasks under established guidelines, escalating exceptions when required.
• Respond to client data queries and coordinate issue triage with Operations and Client Services teams.
• Collaborate with Technology teams on defect resolution, enhancement requests, and UAT for backend data and dataflow changes.
• Contribute to automation and AI-enabled improvements that enhance efficiency and strengthen stewardship capabilities.

Vendor Data Management

• Provide focused stewardship leadership for Vendor Data Management within Documents, including:
  • Vendor and source relationships
  • Issue escalation
  • Quality and timeliness tracking
  • Onboarding support
  • Governance improvements
  • Ongoing coordination with Technology, Product, and business stakeholders
• Strengthen the operating model around vendor data by improving:
  • Visibility into issues
  • Ownership and accountability
  • Dependencies
  • Service expectations
  • Follow-through actions

Process Excellence

• Support User Acceptance Testing (UAT) by validating data, coordinating test execution, and assisting with defect identification and resolution.

• Ensure adherence to governance, data management standards, and operating procedures by following defined controls and compliance requirements.

• Maintain high-quality documentation by updating:

  • Process flows
  • Data definitions
  • Data dictionaries
  • Other stewardship artifacts

  This ensures audit readiness and operational clarity.

Stakeholder Management

• Collaborate with Data Operations and Data Quality teams to support:

  • Governance activities
  • Quality controls
  • Issue remediation

  Serve as a key liaison between governance expectations and day-to-day execution.

• Support Product and Technology teams by assisting with:

  • Data requirements
  • Validations
  • Operational coordination throughout change cycles

• Assist with vendor data reviews by:

  • Conducting data quality checks
  • Performing validations
  • Coordinating onboarding processes

How Impact Will Be Measured (Success Metrics)

Data Accuracy and Integrity

• Maintain high accuracy rates through:
  • Consistent validation
  • Timely corrections
  • Adherence to defined quality thresholds

SLA and Turnaround Adherence

• Meet or exceed service-level timelines for:
  • Data updates
  • Validations
  • Issue resolution
  • Stakeholder responses

Documentation Completeness and Currency

• Keep process documentation, data dictionaries, lineage records, and stewardship artifacts:
  • Up to date
  • Audit ready
  • Fully aligned with governance standards

For This Role You'll Need to Have (Skills & Competencies)

Technical Skills

• Proficiency in SQL to run queries for:

  • Data validation
  • Reconciliation
  • Issue investigation

• Experience working with metadata management and lineage tools to:

  • Maintain data transparency
  • Trace end-to-end data flows

• Advanced use of Microsoft Excel for:

  • Validation
  • Reconciliation
  • Trend analysis
  • Basic data analysis

• Foundational familiarity with BI tools and dashboards to:

  • Review outputs
  • Identify data anomalies

• AI/Automation literacy and future-ready digital fluency

Functional Skills

• Possesses solid domain and process understanding.

• Understands data governance fundamentals, including:

  • Data quality controls
  • Stewardship roles
  • Ownership models

• Supports data standardization by applying:

  • Consistent data definitions
  • Standardized formats
  • Controlled processes

• Has working knowledge of:

  • Data ingestion
  • Data validation
  • Integration workflows

  Assists with troubleshooting and issue resolution.

Behavioral Skills

• Demonstrates strong attention to detail, ensuring accuracy in:

  • Data
  • Documentation
  • Validation activities

• Communicates clearly and collaborates effectively with cross-functional teams, including:

  • Technology
  • Operations
  • Vendor partners

• Applies:

  • Analytical thinking
  • Critical reasoning
  • Creative problem-solving

  To investigate data issues, conduct root cause analysis, and develop business solutions.

• Demonstrates strong learning agility and digital acumen with:

  • A continuous learning mindset
  • Adaptability to evolving tools and technologies

Preferred Education & Experience

• Bachelor's or Master's degree in a quantitative, technical, or business discipline.

• 4+ years of relevant experience in:

  • Data
  • Analytics
  • Operations
  • Related functions

• Experience leveraging AI and Generative AI tools, such as:

  • Microsoft Copilot
  • ChatGPT
  • AI-powered analytics platforms

  To:

  • Improve productivity
  • Automate processes
  • Generate insights
  • Support data-driven decision-making

Key Interfaces & Stakeholders

• Partner with Data Operations, Data Partners, and Data Quality teams on:

  • Data risk management
  • Quality checks
  • Issue resolution

• Coordinate with Technology teams on:

  • Data issues
  • Enhancements
  • UAT activities

• Support Product teams with:

  • Data requirements
  • Validation activities
  • Operational coordination and support