Job Description
What you'll do
• 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 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 to 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
What's required
• 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, PowerShell, Python)
• Commitment to the highest ethical standards
Qualifications
Ivy league colleges education preferred or huge plus.
Additional Information
