Data Security Engineer

Southern New Hampshire University; Sioux Falls (SD); Remote; USD 110,000 - 170,000; Full time

Job summary

Southern New Hampshire University is seeking a Data Security Engineer to implement, operate, and improve controls protecting institutional data across the enterprise data estate, including analytics platforms such as Microsoft Fabric and Databricks, relational databases such as Azure SQL and SQL Server, and the pipelines that move data between them.

You will work alongside other security engineers, SecOps, Data & Analytics, and IT teams, reporting to the Deputy CISO, focusing on encryption,

Qualifications

• Hands-on data security engineering focusing on encryption, key management, and masking.
• Experience implementing least-privilege access models (RBAC/ABAC).
• Familiarity with cloud data platforms and secure data pipelines.

Responsibilities

• Implement and maintain data protection controls across the enterprise data estate.
• Configure encryption for data at rest and in transit; manage keys and CMKs.
• Enforce least-privilege access and conduct entitlement reviews.
• Harden security configurations for Fabric, Databricks, Azure SQL, and SQL Server.
• Embed controls in data ingestion and pipelines; secure notebooks and jobs.
• Automate deployment and evidence collection; integrate with Security Operations.
• Document guides and runbooks; support secure design reviews.
• Attendance, punctuality, and reliability are essential.

Skills

Data protection

Encryption

Access control

RBAC/ABAC

Threat modeling

Automation

Tools

Azure SQL

Databricks

Microsoft Fabric

Job description

About Southern New Hampshire University

Southern New Hampshire University is a team of innovators. World changers. Individuals who believe in progress with purpose. Since 1932, our people-centered strategy has defined us — and helped us grow a team that now serves over 180,000 learners worldwide.

Remote Work Policy

At SNHU, you'll have the option to work remotely in the following states: Alabama, Arizona, Arkansas, Delaware, Florida, Georgia, Hawaii, Idaho, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Mississippi, Missouri, Nebraska, New Hampshire, New Mexico, North Carolina, North Dakota, Ohio, Oklahoma, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, West Virginia, Wisconsin and Wyoming. We ask that our remote employees have access to a reliable internet connection and a dedicated, properly equipped workspace that is free of distractions. Employees must reside in, and work from, one of the above approved states. You will work 100% remotely from any of our approved states.

Opportunity

The Data Security Engineer implements, operates, and helps improve the security controls that protect institutional data across the enterprise data estate, including analytics platforms such as Microsoft Fabric and Databricks, relational database platforms such as Azure SQL and SQL Server, and the pipelines and integrations that move data between them. This is a hands‑on engineering role in the data protection domain: encryption and key management, access and entitlement controls for data, data classification and labeling enforcement, masking and de‑identification, database security configuration, and secure data pipeline engineering. You will work alongside other security engineers, Security Operations, Data & Analytics, Data Governance, Data Engineering, and other IT teams, and provides technical support and guidance to teams building or operating data solutions. You will report to the Deputy CISO.

What you'll do:

• Implements and maintains data protection controls across the enterprise data estate, including classification and labeling enforcement, masking, tokenization, redaction, and de‑identification, so that controls reflect institutional data sensitivity and regulatory requirements.
• Configures and operates encryption controls for data at rest and in transit, including platform‑native encryption, certificate management, customer‑managed keys (CMK), and key rotation, and manages keys, secrets, and credentials using approved vaulting services and managed identities.
• Implements least‑privilege access models across data platforms, databases, workspaces, schemas, tables, pipelines, and service identities, and performs (quarterly) entitlement reviews to identify and remediate excessive or orphaned access.
• Hardens security configurations for Microsoft Fabric, Databricks, Azure SQL, SQL Server, data lakes, and storage services, and assesses database permissions, schemas, stored procedures, queries, and audit settings for weaknesses that could expose or improperly alter institutional data.
• Embeds security controls into data ingestion, transformation, orchestration, sharing, and export workflows, and secures the service identities, connectors, private endpoints, network paths, notebooks, jobs, and CI/CD processes that support them.
• Protects non‑production environments by provisioning synthetic data or controlled production‑data extracts and enforcing approved masking and tokenization standards before data is copied out of production.
• Automates control deployment, configuration assessment, evidence collection, and compliance validation using scripting, infrastructure‑as‑code (IaC), and platform APIs, and integrates data security telemetry with Security Operations to support investigation, containment, and corrective action for data‑related security events.
• Documents and communicates the work: creates and maintains implementation guides, configuration standards, control mappings, and runbooks; participates in threat modeling and secure design reviews; and provides hands‑on technical support to teams designing, deploying, migrating, or troubleshooting data solutions.
• Attendance, punctuality, and reliability are essential functions of this role.
• Other duties and responsibilities as assigned. Job responsibilities can change at any time, with or without notice.

Detailed Responsibilities by Domain

Data security controls

• Design, implement, and maintain reusable data protection controls that enforce institutional security requirements across the enterprise data estate.
• Translate data classification, sensitivity, and regulatory requirements into enforceable controls, including labeling, masking, tokenization, redaction, and de‑identification.
• Evaluate control coverage and effectiveness, identify gaps or configuration drift, and coordinate remediation with control and platform owners.

Encryption and key management

• Operate encryption controls for data at rest and in transit, including platform‑native encryption, certificate management, customer‑managed keys, key rotation, and separation‑of‑duties requirements.
• Implement secure key, secret, and credential management patterns using approved vaulting services, managed identities, and automated lifecycle controls.

Identity and access controls

• Implement least‑privilege access models across data platforms, databases, workspaces, schemas, tables, pipelines, and service identities using role‑based and attribute‑based access control (RBAC and ABAC) where supported.
• Conduct periodic entitlement reviews, identify excessive or orphaned access, and automate access validation and remediation workflows.

Platform, database, and pipeline security

• Harden and maintain security configurations for Microsoft Fabric, Databricks, Azure SQL, SQL Server, data lakes, storage services, and supporting integration technologies.
• Embed security controls into data ingestion, transformation, orchestration, sharing, and export workflows, including validation of source‑to‑target protection requirements.
• Secure the infrastructure behind data integrations: service identities, connectors, private endpoints, and network paths.
• Secure the workloads that run on that infrastructure: notebooks, jobs, and CI/CD pipelines.
• Assess database permissions, schemas, stored procedures, queries, audit settings, and platform features for weaknesses that could expose or improperly alter institutional data.
• Protect non‑production environments through synthetic data, controlled production‑data extracts, and enforcement of approved masking and tokenization standards.

Security operations, automation, and compliance

• Integrate data security telemetry with enterprise security operations and support investigation, containment, evidence collection, and corrective action for data‑related security events.
• Automate control deployment, configuration assessment, and compliance validation through scripting, infrastructure‑as‑code, platform APIs, and policy‑as‑code.
• Track control health metrics, analyze recurring findings and exceptions