Data Security Engineer IV

Position Requirements

• 7+ years of experience in data security, cybersecurity engineering, or cloud security roles.
• Hands‑on experience in data security engineering within a financial services environment (preferred).
• Experience supporting audits, risk assessments, and regulatory examinations.
• Understanding of identity‑centric and behavior‑based security models, including Zero Trust principles, identity‑aware data access, privileged‑user monitoring, insider‑threat detection, UEBA, anomaly detection, and SIEM/SOAR integrations.
• Hands‑on experience designing, implementing, and operating data security controls across structured data environments, including Database Activity Monitoring (DBAM), data discovery and inventory, data access governance, CASB, DLP, and DSPM capabilities.
• Strong expertise in data protection mechanisms such as encryption (at rest, in transit, and field‑level), tokenization, masking, anonymization, row‑level security, and sensitive data classification, labeling, and label propagation.
• Experience securing modern data platforms and pipelines, including relational and cloud‑native databases, data warehouses/lakehouses, and structured ETL/ELT workflows, ensuring protection of data‑at‑rest and data‑in‑motion across on‑prem, cloud, and hybrid environments.
• Ability to drive enterprise wide projects that extend Zero Trust and identity‑aware access principles to data, integrating IAM controls, privileged user monitoring, and policy enforcement with SIEM/SOAR workflows.
• Ability to drive enterprise‑scale adoption of data security controls and policies, including extending governance frameworks to emerging use cases such as machine learning and large language model (AI) systems
• Familiarity with GLBA, SOX, FFIEC, and NYDFS 500 regulatory requirements.
• Knowledge of NIST SP 800‑53 and the NIST Cybersecurity Framework (CSF).
• Ability to communicate complex technical concepts and risks to non‑technical stakeholders, translating technical issues into clear business impacts.
• Ability to partner with adjacent security domains (e.g., unstructured data security, DLP, DSPM) to ensure consistent policy application and to translate control requirements across data types and environments.