Key Responsibilities

Data Governance Interpretation and Advocacy

• Standard Advocacy & Policy Enablement: Support the creation and maintenance of the Data Stewardship Standard Handbook , which rolls up to the overall Data Governance Policy. Your focus will be on operationalizing the spirit of the rule to accelerate business value, not on process constraints.

• Data Classification and Metadata Stewardship: Responsible for Metadata management and Classification of all core data fields in the property domains. You will champion and contribute to this process to ensure data assets are Findable, Usable, Understandable, and Trustworthy in alignment with Cotality's enterprise goals.

• Compliance and Permissible Use: Partner with data governance, data sourcing, and compliance to ensure appropriate permissible use standards are tagged and enforced.

• Center of Excellence (CoE) Leadership: Drive the adoption of stewardship principles through the CoE, acting as the subject matter expert to democratize governance functions across non-FTE roles in Product, Operations, and Data Science.

Data Asset Strategy & Ontological Enablement (The Data Asset Enabler)

• Strategic Data Asset Readiness & Fit-for-Use: Champion the fitness-for-purpose of data assets for all business use cases, from critical production products to future exploratory needs. This includes:

• Partnering with Data Quality and Engineering teams to define and continually refine quality metrics and scorecards based on domain knowledge.

• Proactively driving action plans for data improvement based on quality scores, assessing urgency (e.g., KBE status), and recommending whether to adjust governance rules or the data itself.

• Strategically cataloging and classifying all data (including unused or exploratory data) based on its current and potential use in Cotality's products (e.g., Critical, Informative, Exploratory) to accelerate time-to-value.

• Data Feasibility and Product Advisory: Conduct in-depth analysis and research to advise Product, Data Science, and Engineering teams on the Fitness-for-Use of data assets. Specifically, you will recommend fields based on quality, fill rate, lineage, and other metadata to support critical use cases.

• Define and Govern Ontology (The Keeper of the Dictionary): Partner with key stakeholders to define the unifying language and global ontology for core property data concepts to ensure consistent semantic interpretation across all business units, data supply chains and consuming systems. You will act as the ontological arbiter.

• AI Readiness and Semantic Interpretation: Collaborate with key stakeholders to design the Clarification Layer within the semantic framework. This layer enables CoreAI and ML models to intelligently interrogate and interpret diverse data definitions, ensuring data is AI-Ready.

AI & Technology Enablement

• Operational AI Advocacy: Identify and advise on opportunities where AI and ML operations can be leveraged to enhance the internal data supply chain, improve data quality monitoring, and increase governance efficiency.

• Governance Platform Super User: Act as the primary feedback loop for the Data Governance Tool (e.g., Collibra). Define and mandate feature requirements to eliminate manual cataloging and curation tasks.

• Embedding Governance: Partner with Data Engineering and Technical Stewards to embed governance into the "native run of show" (e.g., championing Requirements as Code) to ensure automated data profiling, lineage capture, and cataloging of data assets in alignment with Enterprise Data Stewardship standards.