Key Responsibilities Serve as the technical expert for Collibra managing its configuration upgrades and performance independently Architect and implement enterprise-wide data governance solutions using Collibra aligned with business and regulatory needs Design and develop custom workflows BPMN integrations REST SOAP APIs and extensions within Collibra Lead the end-to-end implementation of metadata management data cataloging and lineage tracking using Collibra Collaborate with enterprise architects data engineers and business stakeholders to integrate Collibra with platforms like Azure Databricks Snowflake and BI tools Define and enforce Collibra operating model including roles responsibilities stewardship and governance workflows Define and evolve the asset model for business use cases Provide expert-level support and troubleshooting for Collibra users and integrations Conduct advanced training sessions for technical teams and business users Evaluate and roll out current product features for business needs Drive continuous improvement and innovation in Collibra usage across the organization Ensure Collibra supports regulatory compliance and audit requirements through robust lineage and traceability Required Qualifications Skills 7 years of experience in data governance metadata management or related fields Extensive hands-on experience with Collibra Data Intelligence Platform in a large enterprise environment Proven ability to manage Collibra independently including configuration workflow development and integration Deep understanding of Collibra s operating model technical architecture and customization capabilities Strong experience with REST SOAP APIs and BPMN workflows Expertise in data cataloging lineage metadata standards and governance frameworks Experience integrating Collibra with cloud data platforms and enterprise systems Excellent problem-solving communication and stakeholder management skills Preferred Qualifications Collibra Ranger or Architect certification highly desirable Experience in regulated industries such as life sciences or pharmaceuticals Background in data engineering data architecture or enterprise data platforms Familiarity with data quality tools and frameworks