Data Scientist (Privacy Engineer) N374

Housing for Health (HFH) is a program office within Community Programs, a division under the Los Angeles County Department of Health Services (DHS) for the County of Los Angeles.

HFH was created to support people experiencing homelessness with complex clinical needs.

We support people in obtaining housing, improving their health and thriving in their communities.

HFH is a core component of Los Angeles County’s effort to respond to the homeless emergency.

Where appropriate to the job function, a hybrid work schedule may be available, with employees working both remotely and from the office, as needed.   

The Privacy Engineer leads governance and access control within the Community Programs Data Engineering team.

This role ensures data used by programs such as Housing for Health and other Community Programs initiatives is protected, responsibly shared, and governed in line with legal, ethical, and operational standards.

The position supports implementation of access controls, classification, and de-identification strategies that enable high-impact analytics while safeguarding confidentiality.

 The Privacy Engineer plays a critical role in balancing compliance with innovation—designing solutions that unlock valuable data while minimizing risk.

The role involves collaboration with legal, compliance, and engineering teams and supports one of the nation’s most ambitious homelessness data systems.

$8,840.90 - $11,912.82 Monthly

ESSENTIAL FUNCTIONS


* Implement and maintain RBAC and access control across datasets using Unity Catalog, Terraform, and Azure.


* Develop and maintain data catalog.


* Work closely with analytics and lead engineers during the design of semantic data models to proactively embed privacy controls, access restrictions, and risk mitigation strategies into data architecture.


* Identify and address potential data privacy vulnerabilities in new workflows, including conducting targeted assessments to prevent data leaks or breaches and implementing strategies to minimize unnecessary data exposure.


* Support integration of Master Data Management (MDM) systems to link individual records across datasets and ensure consistency of person-level identifiers.


* Develop and maintain identity resolution logic to match records across systems while preserving privacy and ensuring compliance with access policies.


* Collaborate with analytics and lead engineers to ensure identity-linked data is properly classified, masked, and handled throughout its lifecycle.


* Lead design of de-identification, masking, and minimization workflows to prepare datasets for countywide or public use.


* Advise engineering teams on embedding privacy controls during model and pipeline design.


* Identify CJIS and other sensitive data classifications and ensure they are properly isolated, redacted, or routed through compliant compute environments when required.


* Evaluate workflows for vulnerabilities and deve...