About the Role:
Grade Level (for internal use):
10 The Role Scope:
The Securities Reference Data Steward is responsible for supporting the quality, integrity, consistency and effective management of reference data across its lifecycle. The role combines domain expertise, data analysis, data quality management and business analysis to ensure reference data is accurately defined, sourced, mastered and distributed to support internal and external products.
The individual will work closely with Data Operations, Technology, Product, Data Governance and other Data Stewardship teams to investigate complex data issues, translate business requirements into actionable data rules, and support strategic data onboarding and transformation initiatives.
What You'll Do (Key Responsibilities):
1. Reference Data Stewardship
Develop strong subject-matter expertise across assigned reference-data domains.
Understand how reference data is sourced, modelled, linked/mastered and distributed across downstream products.
Maintain and improve business definitions, data rules, metadata and stewardship standards.
Support consistent application of reference-data standards across platforms and workflows.
2. Data Quality & Root-Cause Analysis
Proactively identify and investigate data-quality issues, exceptions and inconsistencies.
Perform detailed root-cause analysis across source/vendor data, business rules, mastering/linking logic and downstream outputs.
Distinguish between tactical data corrections and issues requiring strategic process or technology remediation.
Partner with Technology and Operations teams to implement sustainable fixes and appropriate data-quality controls.
3. Data Onboarding & Change Initiatives
Provide stewardship support for the onboarding of new vendors, datasets and reference-data attributes.
Analyse incoming datasets and determine appropriate mapping, standardisation, linking and mastering requirements.
Define business requirements and acceptance criteria for enhancements to reference-data platforms.
Perform data validation and UAT to ensure solutions meet business and data-quality expectations.
Assess downstream impacts arising from source, schema, business-rule or vendor changes.
4. Data Governance & Controls
Support implementation of enterprise data-governance standards within the assigned domain.
Maintain appropriate business definitions, data lineage, quality rules and supporting documentation.
Identify gaps in existing controls and recommend improvements.
Ensure data issues are captured, prioritised and driven to appropriate resolution.
5. Stakeholder & Cross-functional Collaboration
Partner with Product, Technology, Data Operations, Data Governance and other Stewardship teams on data initiatives and issue resolution.
Translate complex technical or data problems into clear business impact and requirements.
Coordinate investigations involving multiple platforms, vendors or downstream consumers.
Act as a SME for assigned datasets and initiatives.
6. Continuous Improvement
Identify opportunities to reduce manual intervention and recurring data-quality issues.
Recommend improvements to data sourcing, validation, mastering and stewardship workflows.
Contribute to automation and scalable data-quality controls.
Document learning from incidents and complex investigations to strengthen team knowledge.
For This Role You'll Need to Have (Skills & Competencies)
Domain / Functional
Strong understanding of reference-data concepts and data lifecycle management.
Experience analysing complex datasets and data-quality issues.
Ability to perform detailed root-cause analysis and translate findings into business requirements.
Understanding of data governance, metadata, data lineage and data-quality principles.
Experience with vendor/source-data ingestion, mapping, validation or mastering is highly desirable.
Technical
Strong SQL and data-analysis skills.
Ability to work with large datasets and investigate relationships across multiple data…