Data Security Engineer

Responsibilities include:

• Design and implement comprehensive data security architectures, focusing 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, on-premise and in the cloud.
• Enhance logging, monitoring and SecOps 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.

Qualifications

• Bachelor's degree in computer science, cybersecurity, or a 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.
• Subject‑matter expertise in object storage (e.g., S3, Azure Blob) and related security.
• Understanding of Active Directory Delegation (constrained vs. unconstrained) and associated best practices.
• Experience with third‑party SQL Server security governance and monitoring products (e.g., 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 (e.g., SQL, PowerShell, Python).
• Commitment to the highest ethical standards.
• Education from an Ivy League college is preferred or a huge plus.

Additional Information

All information will be kept confidential according to EEO guidelines.

Job Location

Location TBD.