Data Security Engineer

Responsibilities

• Design and implement comprehensive data security architectures, with particular focus on database platforms (primarily SQL Server).
• Develop and maintain enterprise-wide encryption strategies for securing structured and unstructured data both in transit and at rest, both and both on-premise and in the cloud.
• Enhance logging, monitoring and Sec Ops capabilities of enterprise databases and other data stores.
• Configure and optimize Identity and Access Management (IAM) solutions across data platforms and repositories to align with least privilege principles.
• Implement Data Loss Prevention (DLP) strategies and controls.
• Implement and maintain Information Rights Management (IRM) and Digital Rights Management (DRM) solutions.
• Design and implement data tokenization strategies where appropriate.
• Secure data processing pipelines and ensure appropriate controls for data workflows.
• Create and maintain data security documentation, including policies, procedures, and standards.
• Collaborate with development teams to ensure security best practices in data handling.
• Conduct vulnerability assessments of the firm’s database architecture and associated data storage and processing systems.
• Assist in monitoring and managing security patching and upgrade processes for database platforms.

• Bachelor's degree in computer science, cybersecurity, or related technical field.
• 6+ years of experience in data/database security engineering and governance.
• Deep expertise in database security, particularly SQL Server.
• Comprehensive understanding of data warehouse/data lake architectures and tools, particularly Databricks (required).
• Subject matter expertise in Object Storage (eg: S3, Azure Blob, etc) and related security.
• Understanding of Active Directory Delegation (constrained vs. unconstrained) and associated best practices.
• Experience with 3rd-party SQL Server security governance and monitoring products (eg: Idera, Solarwinds).
• Extensive knowledge of encryption technologies for both structured and unstructured data.
• Broad knowledge of secure data/file sharing solutions and ETL workflows.
• Experience designing and implementing data tokenization solutions.
• Experience with data classification and DLP technologies.
• Scripting/automation capabilities (eg: SQL, Power Shell, Python).
• Commitment to the highest ethical standards.

Ivy league colleges education preferred or huge plus.

All your information will be kept confidential according to EEO guidelines.