Job Description
Location: India Remote
About MediaRadar
MediaRadar, now including the data and capabilities of Vivvix, powers the mission-critical marketing and sales decisions that drive competitive advantage. Our competitive advertising intelligence platform enables clients to achieve peak performance with always-on data and insights that span the media, creative, and business strategies of five million brands across 30+ media channels. By bringing the advertising past, present, and future into focus, our clients rapidly act on the competitive moves and emerging advertising trends impacting their business.
About the Role
Job Summary:
We are seeking an experienced Senior Data Governance Lead to drive the next phase of our data governance evolution. This role is ideal for a hands-on leader who can translate abstract governance concepts into clear taxonomies, measurable data rules, and enforceable quality standards that scale across the organization.
You will help to lead a taxonomy and rules transformation—establishing shared definitions, structured classification systems, and outcome-driven data quality rules that directly improve data trust, usability, and business impact. This role partners closely with data, product, engineering, operations, and analytics teams to embed governance into how data is designed, produced, and consumed—not as overhead, but as enablement.
This role is critical to building long-term data governance muscle across the organization by equipping teams with practical frameworks, guidance, and repeatable ways of working.
Responsibilities:
- Lead the design and governance of an enterprise taxonomy and data rule framework, including business terms, entities, products, and classification hierarchies that support consistent data use.
- Translate business needs into clear, objective, and measurable data and quality rules that can be implemented, tested, and monitored.
- Develop governance frameworks that connect taxonomy → business rules → data quality standards → measurable outcomes.
- Partner with data engineering, analytics, and product teams to embed governance requirements into data pipelines, tooling, and workflows.
- Establish standards for rule authoring, validation, conflict detection, and lifecycle management.
- Drive clarity and consistency in definitions, metadata, and documentation across domains.
- Support the creation of data quality metrics, thresholds, and reporting aligned to business use cases.
- Coach and enable data owners, stewards, analysts, and associates to apply governance standards confidently and consistently.
- Contribute to governance operating models, playbooks, and training materials designed for both technical and non-technical audiences.
- Act as a thought partner on governance best practices, tooling needs, and maturity progression.
Success Measures:
Success in this role will be measured by:
- Taxonomy Adoption & Clarity – Demonstrated reduction in ambiguity and rework through consistent use of approved taxonomies and definitions.
- Rule Effectiveness – Clear, testable data and quality rules that lead to measurable improvements in data accuracy, consistency, and trust.
- Scalability of Governance – Frameworks and standards that teams can apply independently without constant governance intervention.
- Data Quality Improvements – Observable improvements in key data quality indicators tied to governed datasets.
- Stakeholder Enablement – Positive feedback from teams on the usability, clarity, and practicality of governance guidance.
- Operationalization – Governance artifacts (taxonomy, rules, standards) actively used in production workflows rather than existing only as documentation.
Key Qualifications and Role Requirements:
- 5–10 years of experience in data governance, data management, data quality, analytics, or data operations.
- Proven experience designing or implementing taxonomy frameworks, classification systems, or business term definitions.
- Strong ability to translate complex business concepts into structured, objective rules.
- Experience working cross-functionally with data engineering, analytics, product, and operational teams.
- Demonstrated success moving organizations from ad hoc or narrative governance toward structured, standards-based approaches.
- Familiarity with data quality dimensions (e.g., accuracy, completeness, timeliness, consistency) and how to operationalize them.
- Knowledge of or certification in DAMA / DMBOK is a strong plus.
- Comfort operating in environments with evolving maturity and ambiguity.
- Excellent written and verbal communication skills.
