Data Scientist - Analytics Engineer (N375)

Salary Range: $8,840.09-$11,912.82 monthly

SUMMARY

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 Analytics Engineer plays a key role on the Community Programs Data Engineering team, building the semantic layer that supports performance tracking, evaluation, and policy guidance across initiatives such as Housing for Health and other countywide data integration efforts.

This position translates analytic requirements into curated silver and gold data models using Databricks and supports integration of data from normalized backend systems.

This is a chance to architect a scalable data environment from the ground up in a mission-driven context.

The engineering team plays a central role in the County’s data strategy, with opportunities for mentorship, innovation, and cross-sector impact.

Work is primarily remote within California and on Pacific Time.

In-person meetings occur monthly for critical collaboration moments.

Travel for these meetings is not reimbursed.

ESSENTIAL FUNCTIONS


* Build and maintain semantic data models (silver and gold layers) in Spark/Databricks, primarily through ELT/ETL pipelines written in PySpark.


* Understand and identify entity relationships among large collections of normalized backend tables to design accurate, denormalized, analyst-ready structures.


* Contribute to schema and catalog design decisions, including naming conventions for static vs.

live feeds and ad hoc data use cases.

This includes creating and maintaining documentation that clarifies data model logic, table relationships, and mapping assumptions to support downstream users and internal knowledge transfer.


* Collaborate with program and analytic teams to understand and translate both business rules used to define data fields as well as needs of analytic teams using semantic layer to produce reports and dashboards.


* Collaborate with the Privacy Engineer to ensure analytic datasets align with RBAC policies, de-identification requirements, and data classification standards set for Departmental and Countywide use.


* Contribute to, update, and maintain centralized code repositories used for data transformations.


* Participate in Dev/Prod promotion workflows using GitHub, ensuring proper validation and configuration for CI/CD deployment.


* Apply expectations and version control to standardize, test, and document pipelines.


* Collaborate with E...