Data Security Engineer

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