• Design and maintain end-to-end data security architecture across Microsoft Azure, Microsoft Fabric, Azure Synapse Analytics, Azure Data Lake Storage (ADLS Gen2), and Databricks Lakehouse Platform. • Define and enforce enterprise data classification, labeling, and handling standards aligned with Microsoft Purview Information Protection. • Develop reference architectures and security blueprints for data ingestion, transformation, storage, and consumption layers. • Lead threat modeling sessions for data pipelines and analytics workloads, identifying and mitigating risks proactively. • Establish a Zero Trust data security model across all data platforms and integration points. • Architect and govern data security controls within Microsoft Fabric, including workspace-level and item-level permissions, sensitivity labels, and OneLake security. • Design role-based access control (RBAC) and attribute-based access control (ABAC) strategies across Azure Data Factory, Azure Synapse, Azure Databricks, and Azure SQL. • Implement and operationalize Microsoft Purview for data catalog governance, data lineage, and automated sensitivity classification across hybrid and multi-cloud data estates. • Configure and manage Azure Private Endpoints, VNet integration, and network security groups for data services to eliminate public exposure. • Oversee encryption strategies including Azure Key Vault integration, customer-managed keys (CMK), and data-at-rest / data-in-transit encryption standards. • Partner with identity teams to enforce Entra ID Conditional Access policies, Privileged Identity Management (PIM), and managed identities for data service authentication. • Lead the implementation and tuning of Microsoft Defender for Cloud data security posture management (DSPM) capabilities. • Architect and implement Unity Catalog as the enterprise-wide data governance layer across Databricks workspaces, including metastore design, catalog/schema/table-level permissions, and row/column-level security. • Design Databricks workspace security including network isolation (no-public-IP, vNet injection, private link), cluster policies, and IP access lists. • Define and enforce Databricks credential passthrough, service principal governance, and OAuth integration with Azure Entra ID. • Implement dynamic data masking and column-level security policies within Unity Catalog to protect PII, PHI, and sensitive financial data. • Establish Delta Lake security patterns including table ACLs, fine-grained access control, and audit logging strategies via Databricks system tables. • Oversee the security of Databricks workflows, notebooks, and job clusters, including secrets management integration with Azure Key Vault-backed secret scopes. • Conduct security reviews of MLflow models and Feature Store configurations to address data leakage risks in ML pipelines. • Ensure data platform compliance with relevant regulatory frameworks including GDPR, CCPA, HIPAA, SOC 2 Type II, and PCI-DSS where applicable. • Design and maintain audit trail and data access logging architectures across Microsoft and Databricks platforms. • Conduct regular security risk assessments, gap analyses, and maturity evaluations of the data security program. • Develop and maintain security runbooks, policies, and standards documentation for data platform operations. • Coordinate with legal, compliance, and privacy teams to respond to data subject access requests (DSARs) and regulatory inquiries. • Serve as the primary security advisor to data engineering, analytics engineering, and BI teams throughout the development lifecycle. • Lead security architecture review boards for new data initiatives, third-party data integrations, and major platform changes. • Develop and lead a structured mentoring program for junior and mid-level engineers and architects, providing one-on-one coaching, career guidance, and skills development roadmaps tailored to each individual’s growth goals. • Conduct regular knowledge-sharing sessions, lunch-and-learns, and internal workshops to upskill teams on evolving data security threats, tooling, and compliance requirements across the Microsoft and Databricks ecosystems. • Partner with engineering managers and HR to define data security competency frameworks, leveling guides, and certification pathways that support talent development and retention across the data platform organization. • Establish and maintain a community of practice around data security, fostering peer learning, documentation culture, and cross-team collaboration on shared security challenges and architectural patterns. • Collaborate with SecOps and SOC teams to build data-specific detection rules, incident response playbooks, and forensic investigation capabilities. • Present security posture, risk findings, and remediation roadmaps to executive leadership and board-level stakeholders.