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As a Data Governance Lead at Incedo AI&D, you will be responsible for defining and executing data governance strategies to ensure the security, integrity, quality, and compliance of AI & Data ecosystem for a large client organization. You will work across AI, data engineering, analytics, and business teams to establish governance frameworks, enforce policies, and ensure that data assets are properly managed and leveraged for AI / ML, automation, and analytics. This role requires a strategic mindset, technical expertise, and strong stakeholder management skills to drive adoption of best practices and ensure compliance with regulatory and enterprise data policies. Role and responsibilities: Develop and implement Data Governance Framework, including policies, standards, and best practices for data quality, metadata management, privacy, and security. Establish and manage data stewardship programs, ensuring data ownership, accountability, and compliance across AI, analytics, and business functions. Work closely with Legal, Compliance, and Security teams to ensure adherence to regulatory frameworks and client’s internal data privacy regulations. Define data lineage, classification, and cataloging strategies to improve data discoverability and traceability across AI & Data platforms. Lead the governance of AI / ML data assets, ensuring data quality, integrity, and ethical AI practices, including bias detection, fairness, and explainability. Collaborate with data engineering and AI teams to integrate governance controls into Google Cloud (GCP), BigQuery, and AI / ML pipelines. Drive the adoption of data governance tools such as Collibra, Alation, Informatica, IBM Data Catalog, Google Cloud Data Catalog, and automated compliance frameworks. Establish metadata management and Master Data Management (MDM) strategies to maintain a single source of truth across AI / ML and analytics initiatives. Build governance solutions for unstructured and structured data used in AI / ML models, RAG (Retrieval-Augmented Generation) workflows, and enterprise analytics. Advocate for data ethics, privacy-first AI, and responsible data handling within Verizon’s AI&D organization. Conduct training and awareness programs to foster a culture of data governance and compliance across the organization. Technical skills requirements: Data Governance Frameworks & Tools: Experience with Collibra, Alation, Informatica, IBM Data Catalog, Google Cloud Data Catalog, or similar governance solutions. Cloud & Data Engineering: Familiarity with Google Cloud Platform (GCP), BigQuery, AWS, or Azure data governance principles. AI & ML Data Governance: Knowledge of governance strategies for AI / ML models, data pipelines, feature stores, and RAG workflows. Data Quality & Metadata Management: Hands-on experience with data profiling, lineage tracking, and MDM solutions. Regulatory & Compliance Knowledge: Deep understanding of regulatory frameworks like GDPR, CCPA, HIPAA, FCC regulations, and telecom industry data governance best practices. Data Privacy & Security: Experience with PII data handling, encryption, anonymization, access control, and cloud security. SQL & Scripting: Proficiency in SQL, Python, and automation tools for data governance workflows. AI / ML Governance: Understanding of bias detection, explainability, fairness, and ethical AI practices. Data Architecture & Integration: Experience with data lakes, warehouses, APIs, and real-time data streaming governance. Nice-to-have skills: Experience with AI Governance frameworks (e.g., Responsible AI principles, AI risk management). Knowledge of RAG-based AI applications and governance of vector databases. Google Cloud certifications (e.g., Google Cloud Professional Data Engineer). Experience with Kubernetes (K8S), Airflow, or Prefect for workflow orchestration. Familiarity with telecom data governance processes and telecom data regulations. Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Management, Information Systems, AI, or a related field. 15+ years of experience in data governance, data management, or data strategy, with at least 3 years in a leadership role. Experience in telecom, AI, cloud, or large-scale data-driven enterprises is a plus.

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