Job Summary

The Data Steward Lead is an individual contributor role that supports datasets endtoend with robust 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 artificialintelligenceenabled stewardship practices to enhance efficiency and data quality.

Grade Level (for internal use): 10

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 costoptimization 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 mediumsized projects and manage user acceptance testing.
- Respond to complex client queries, review client escalations, and provide robust rootcause analysis for resolution.
- Ensure delivery of assigned projects is on track through close coordination with internal teams and Technology groups.
- Lead smaller artificialintelligenceenabled 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 highquality, accurate, and uptodate 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, and large-scale data quality investigations across multiple datasets and domains.
- Possesses hands-on experience working with master data management, data stewardship, data governance, metadata management, and data quality frameworks, including defining business rules, validation controls, lineage, and monitoring processes.
- Understands modern data architecture and integration patterns, including APIs, file-based ingestion, ETL/ELT pipelines, data modeling concepts, and cloud-based data platforms.
- Proven ability to work within Agile delivery models, collaborating effectively with Product Owners, Engineers, Architects,



and Business Stakeholders through sprint planning, backlog refinement, user story definition, testing, and iterative delivery cycles.
- Experience performing data mapping, entity resolution, source-to-target analysis, and reconciliation across multiple internal and external data sources.
- Demonstrates the ability to leverage AI-enabled tools, Generative AI platforms, and prompt engineering techniques to improve data stewardship workflows, automate analysis, accelerate issue investigation, and enhance operational efficiency.
- Strong understanding of data governance principles, including data ownership, data contracts, business glossary management, reference data management, and regulatory/compliance considerations.
- Ability to translate complex business requirements into scalable data solutions, while effectively communicating technical concepts to both technical and non-technical stakeholders.

Functional Skills
- Possesses strong domain and process understanding, enabling effective stewardship decisions across assigned datasets.
- Knowledgeable in data governance policies and frameworks, ensuring consistent application across ingestion, validation, and distribution workflows.
- Experienced in vendor data management, including review cycles, coordination with external providers, and issue identification or resolution.

Behavioral Skills
- Applies structured, analytical problemsolving to diagnose issues, drive rootcause analysis, and propose practical interim and permanent fixes as remediation steps.
- Communicates proactively and clearly with technical and nontechnical stakeholders, enabling effective collaboration.
- Applies critical thinking creative problem solving to build solutions for business problems.
- Demonstrates solid learning agility and digital acumen, with a continuous learning mindset and the ability to adapt to evolving tools and technologies.
- Shows willingness and capability to mentor junior stewards, foster knowledge sharing, and building broader team capability.

Preferred Education Experience
- Bachelors degree in a relevant field; professional coursework or certification in data governance is preferred.
- 5+ years of experience in data stewardship, data management, data governance, or related function.

Key Interfaces Stakeholders
- Data Quality, Data Governance
- Technology teams, Product teams
- Data Operations, Customer Success, and Compliance functions.

📌 Senior Data Steward, Company & Security Foundational Data (Hyderabad)
🏢 S&P Global Market Intelligence
📍 Hyderabad