Collibra Project Lead – Data & AI Governance (Banking Domain)

We are seeking a highly experienced and strategic Collibra Project Lead to lead enterprise-wide Data Governance and AI Governance initiatives for a leading Banking organization. The ideal candidate will possess deep expertise in Collibra platform implementation, data lineage, data governance operating models, and end-to-end data lifecycle management across complex banking ecosystems. This role requires strong leadership capabilities to manage governance rollouts, coordinate cross-functional stakeholders, drive enterprise adoption, and ensure successful implementation of governance frameworks aligned with regulatory, operational, and AI governance requirements. The candidate should have a strong understanding of the complete data journey including data ingestion, transformation, modeling, lineage, quality, metadata management, and AI governance controls across enterprise platforms such as cloud, data warehouses, data lakes, ETL pipelines, and analytics ecosystems. Key Responsibilities Program & Project Leadership             •          Lead enterprise-scale Collibra implementation and rollout programs across multiple banking business units and domains.             •          Define and execute governance roadmaps, implementation strategies, and phased rollout plans.             •          Manage end-to-end delivery including planning, execution, governance, risk management, stakeholder communication, and post-production adoption.             •          Drive governance maturity transformation initiatives aligned with enterprise data strategy.               •          Coordinate with business, technology, risk, compliance, security, and architecture teams to ensure governance alignment.             •          Lead steering committee discussions and provide executive-level status reporting. Data Governance & AI Governance             •          Design and implement enterprise Data Governance Frameworks using Collibra.             •          Establish governance policies, standards, stewardship models, workflows, and operating procedures.             •          Implement and operationalize:             ◦           Business Glossary             ◦           Data Catalog             ◦           Data Ownership & Stewardship             ◦           Data Quality Governance             ◦           Metadata Management             ◦           Reference Data Governance             ◦           Data Classification & Privacy             ◦           Policy Management             ◦           AI Governance controls and compliance frameworks             •          Support responsible AI initiatives including:             ◦           AI model governance             ◦           Model lineage and traceability             ◦           AI risk management             ◦           Regulatory compliance for AI/ML usage             ◦           Data transparency and explainability Data Lineage & Metadata Management             •          Lead implementation of technical and business lineage across enterprise data ecosystems.             •          Integrate Collibra with ETL/ELT, BI, cloud, and data warehouse platforms for automated metadata harvesting and lineage extraction.             •          Ensure lineage visibility from source systems to downstream reporting and AI/analytics layers.             •          Work closely with engineering teams to define lineage standards and metadata onboarding processes.             •          Enable impact analysis, traceability, and regulatory reporting capabilities through lineage implementation. End-to-End Data Lifecycle Understanding             •          Demonstrate strong understanding of complete enterprise data flow including:             ◦           Source system ingestion             ◦           Batch and real-time data pipelines             ◦           ETL/ELT transformations             ◦           Data modeling             ◦           Data warehousing             ◦           Data lake architectures             ◦           Reporting and analytics consumption             ◦           AI/ML data pipelines             •          Collaborate with architecture and engineering teams to govern data across hybrid and cloud ecosystems.             •          Validate governance integration across structured, semi-structured, and unstructured data assets. Stakeholder & Business Engagement             •          Act as the primary liaison between business stakeholders, data stewards, governance councils, and technical teams.             •          Conduct workshops, governance assessments, and onboarding sessions.             •          Drive enterprise adoption and governance culture transformation.             •          Facilitate issue resolution and governance decision-making across domains.             •          Mentor governance analysts, stewards, and implementation teams. Regulatory & Banking Compliance             •          Ensure governance implementation aligns with banking and financial industry regulations including:             ◦           BCBS 239             ◦           GDPR             ◦           CCPA             ◦           SOX             ◦           Basel standards             ◦           Data privacy and retention policies             •          Support audit, compliance, and risk management initiatives through governed metadata and lineage transparency. Job Requirements: ·      12+ years overall experience with 5+ years in Collibra implementation and enterprise data governance leadership within Banking or Financial Services. ·      Strong hands-on expertise in Collibra Data Intelligence Platform,Collibra Data Governance Center, Collibra Lineage, Collibra Catalog, Workflow customization, Metadata ingestion and integrations ·      Experience implementing lineage across Informatica,Talend,Ab Initio, DataStage, Snowflake, Databricks, Azure / AWS / GCP, Power BI / Tableau ·      Strong understanding of Data modeling concepts , ETL/ELT pipelines, Data warehousing, Lakehouse architecture , API integrations, SQL and metadata structures ·      Familiarity with AI governance frameworks and responsible AI practices. ·      Banking Domain Expertise: Strong understanding of banking data domains such as Customer, Risk, Finance, Treasury, Payments, AML/KYC, Regulatory reporting, Loans and deposits ·      Experience working in highly regulated financial environments. ·      Excellent stakeholder management and communication skills. ·      Strong program management and coordination capabilities. ·      Ability to influence senior leadership and governance councils. ·      Strong analytical, problem-solving, and decision-making skills.