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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Governance Professional - **Company:** CoreLogic, Inc. - **Location:** Irvine, CA, United States - **Experience:** Expert - **Salary:** $89,400.0 - $130,000.0 - **Contract:** Permanent contract - **Skills:** Agile Methodology, Artificial Intelligence, Amazon Web Services, Data Analysis, Cloud Database, Cyber Security, Information Systems, Data Architecture, Data Dictionary, Data Governance, Identity and Access Management, Machine Learning, Systems Development Life Cycle, DataOps, Software Engineering, Unstructured Data, Enterprise Data Management, Data Ingestion, Generative AI, Data Lakes, Information Technology, Collibra, Data Management, Machine Learning Operations, Databricks - **Published:** June 5, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=eeb5e3f72cb929eb ## About the Role Do you have experience in SDLC?, Do you have a Bachelor's degree?, * 7-10 years of experience in any of the following disciplines: Data Management/Governance, AI/Model Governance, Regulatory Compliance, Risk Management, or Data Science/Analytics. * Bachelor's degree or equivalent experience in a business, technology, or quantitative field (e.g., Computer Science, Data Science, Information Systems). * Solid understanding of the Software Development Life Cycle (SDLC), Data Life Cycle (DLC), and Machine Learning Operations (MLOps) lifecycle. * Familiarity with modern data architectures (e.g., cloud data warehouses, data lakes, unstructured data, vector databases) and the lifecycle of predictive and generative AI models. * Knowledge of AI risk management frameworks (e.g., NIST AI RMF) and practical approaches to Responsible/Ethical AI. * Strong interpersonal and collaborative skills, with a proven ability to work in a matrixed environment, successfully bridging technical (engineering/data science) and non-technical (legal/business) teams. * Strong verbal and written communication skills, capable of translating complex AI/Data concepts to executive stakeholders. * Strong analytical skills, the ability to thrive in ambiguity, and a genuine excitement for data exploration and AI innovation. * Functional and technical knowledge of modern tools used in Data and AI governance (e.g., Collibra, Alation, MLflow, AWS SageMaker, Databricks, or similar enterprise governance platforms) is a strong plus. ## Description The Enterprise Data & Model Governance Program team has the mission to establish data and artificial intelligence as strategic assets, delivering continuous business value while ensuring the responsible, secure, and compliant use of data and models. The team engages closely with business stakeholders, data scientists, machine learning (ML) engineers, technology teams, data architects, operations, and legal/compliance to build, scale, and implement comprehensive Data, Model, and AI governance capabilities. T he Senior Data Governance Professional independently plans, completes assignments, sets goals, and collaborates with stakeholders. This role combines technical expertise with strategic thinking to establish and maintain data governance frameworks that support business objectives, ensuring data quality, integrity, and compliance across the organization., * Develop operating models and processes to build foundational capabilities, including enterprise data and AI catalogs, model registries, feature stores, data/model access management, and the creation of unified policies and standards. * Establish and enforce comprehensive policies and standards for effective management throughout the entire Data and AI lifecycles (from data ingestion and model training to deployment, monitoring, and retirement). * Design and implement frameworks for Model and AI Governance to ensure algorithmic fairness, transparency, explainability, and the active monitoring/mitigation of model drift and bias. * Act as a critical liaison with Compliance, Legal, and Information Security teams to manage data and AI risks, ensuring adherence to global data privacy laws (e.g., GDPR, CCPA) and emerging AI regulations/frameworks (e.g., EU AI Act, NIST AI RMF). * Roll out and integrate governance processes with enterprise workflows, including MLOps, DataOps, PMO, and agile software development life cycles. * Establish robust change management processes to ensure foundational data dictionaries, AI inventories, and model components are kept up to date. * Support Data and AI Stewards across various business units in the practical implementation and scaling of governance capabilities. * Continuously incorporate emerging best practices and developments from the modern data management, machine learning, and AI industries to drive innovation and business value generation. ## Related Videos - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [Enabling intelligent logistics automation: home-grown Industrial IoT platform at Austrian Post](https://www.wearedevelopers.com/videos/2018-enabling-intelligent-logistics-automation-home-grown-industrial-iot-platform-at-austrian-post) ## Related Articles - [Got AI ideas but no money? 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