Senior Data Steward, Data Stewardship, Company & Security Foundational Data

Grade Level (for internal use): 10 The Role Scope: The Data Steward Lead is an individual contributor role that supports datasets end‑to‑end with strong ownership and alignment to product deliveries and roadmaps. The role drives the execution of multiple projects, gaining exposure to product deliveries, managing data ingestion activities, overseeing vendor data reviews, and leading user acceptance testing cycles for backend tables and data distribution. The position also addresses complex client queries and manages related escalations. The Data Steward Lead advances operational excellence by streamlining backend database curation, refining, and enforcing data policies, ensuring compliance, maintaining taxonomy and metadata, and coordinating effectively with Technology and Operations teams. The role also leads targeted automation initiatives and supports the adoption of artificial‑intelligence‑enabled stewardship practices to enhance efficiency and data quality. What You’ll Do (Key Responsibilities) Operational Delivery Define validation rules, checkpoints, and minor policy or process enhancements. Manage dataset ingestion, taxonomy governance, and data lineage. Contribute to strengthening the data governance framework for assigned datasets by designing, refining, and enforcing robust governance controls that align with enterprise standards and data management standards. Execute vendor reviews and coordinate vendor data integration and cost‑optimization activities. Own parts of user acceptance testing cycles for assigned datasets, including backend database changes, downstream data flows, and risk assessments. Govern stewardship tasks and identify process improvements to streamline workflows and remove duplication. Expand scope across multiple projects within a domain and begin defining validation and policy standards. Balance project execution (approximately 70 percent) with governance and vendor coordination (approximately 30 percent). Write requirements for small to medium‑sized projects and manage user acceptance testing. Respond to complex client queries, review client escalations, and provide robust root‑cause analysis for resolution. Ensure delivery of assigned projects is on track through close coordination with internal teams and Technology groups. Lead smaller artificial‑intelligence‑enabled stewardship use cases within a dataset.  Process Excellence Own a defined scope of user acceptance testing activities for the dataset. Ensure adherence to established data, quality, and process standards. Maintain high‑quality, accurate, and up‑to‑date documentation. Stakeholder Management Collaborate with Data Risk & Oversight (DRO) and Data Quality (DQ) teams acting as a key governance partner on governance requirements, control execution, and issue management. Partner with Product and Technology teams to support data delivery, change implementation, and issue triage. Engage proactively with stakeholders (Technology, Product, Operations) to communicate data standards, clarify ownership, and ensure governance principles are embedded into data workflows, issue resolution, and delivery outcomes Support vendor data reviews, onboarding coordination, and validation activities as required. How impact will be measured (Success Metrics) Reduction in data defects and repeat issues across assigned datasets through strengthened validation, improved controls, and proactive remediation. Vendor SLA adherence, including timely completion of vendor reviews, data corrections, integrations, and related turnaround expectations. Improved data coverage and completeness for supported products and datasets, contributing to higher-quality outputs and enhanced downstream usability. For This Role You'll Need to Have (Skills & Competencies)   Technical Skills Demonstrates strong proficiency in SQL and Python, with the ability to perform complex data analysis, data profiling, reconciliation, root-cause analysis,