Data/Analytics Engineer

Public Health Foundation Enterprises, In is seeking a Data/Analytics Engineer in Los Angeles, CA (onsite) to lead end-to-end data architecture and analytics across housing, justice, and clinical programs.

Responsibilities

• Develop and scale a centralized, governed Databricks platform that serves as the single source of truth for housing, justice, and clinical data.
• Design and deploy automated, production-ready ETL/ELT pipelines and CI/CD processes using Databricks, Terraform, and GitHub.
• Convert intricate program rules into scalable data models and reusable data products.
• Create scalable semantic models that track a single client's journey across multiple programs, standardizing touchpoints over time.
• Implement secure-by-design data systems handling PHI and CJI data using Unity Catalog for governance, audit logging, and access control.
• Support advanced analytics by building curated datasets, APIs, and ML/NLP-ready environments.
• Collaborate with leadership and cross-functional teams to drive data-informed policy, operations, and outcomes.
• Provide technical leadership and mentoring, establishing standards for scalable, maintainable systems.
• Map multi-source program utilization (CHAMP, DD, HMIS) to funding streams to ensure strict fiscal and grant tracking compliance.
• Design and maintain a scalable Databricks lakehouse architecture following Medallion principles; integrate structured and unstructured data across domains; align with standards such as FHIR and HL7v2 to support a unified analytics system of record.
• Automate data lifecycles with GitHub Actions and Terraform, applying CI/CD, version control, unit testing, and automated validation prior to production deployment.
• Design and maintain the Unified Data Model for Community Programs; stitch together longitudinal client journeys across CHAMP, DD, HMIS, and other systems; develop multi-dimensional data structures mapping cross-program utilization to diverse funding streams for precise fiscal and operational analytics.
• Establish and enforce enterprise data governance including RBAC/ABAC, data lineage, audit logging, and data loss prevention to support regulated data (PHI, CJI).
• Develop and manage scalable data products, including curated datasets, APIs, and analytical layers for reporting, dashboards, and advanced analytics; optimize SQL and BI tool performance (Tableau, Power BI) for reliable insights.
• Provide technical leadership and delivery oversight to data engineers, analysts, and scientists, promoting best practices in system design.
• Build and maintain the environments required for advanced analytics; collaborate with data scientists and DHS Security teams to ensure models and data products are scalable, governed, and compliant.

Technologies

• Databricks
• Terraform
• GitHub
• GitHub Actions
• Unity Catalog
• SQL
• Tableau
• Power BI
• Python
• Pandas
• PySpark

Requirements

• Substantial experience in Enterprise Data Architecture.
• Substantial experience in Cloud Infrastructure.
• Substantial experience in Analytics Engineering.
• Hold a relevant degree.
• Proven track record managing complex data lifecycles within large-scale Databricks environments.
• Substantial experience in Cloud Data Engineering.
• Substantial experience in Infrastructure Automation.
• Option I: Two years in a lead capacity carrying out complex data infrastructure and architecture projects, including independently designing and implementing automated ETL/ELT pipelines, managing Lakehouse environments (Databricks), and enforcing enterprise data security (RBAC/ABAC), at a level equivalent to the Los Angeles County class of Principal Information Systems Analyst.
• Option II: Bachelor’s degree in Information Technology, Computer Science, Data Engineering, or Data Science, and six years of experience applying and overseeing data engineering, infrastructure automation (CI/CD), and enterprise data management; two years of this experience in a lead role. A Master’s or Doctoral degree may substitute for up to two years of general experience.
• DHS Live Scan clearance is required.
• Expert proficiency in Python for data manipulation (Pandas, PySpark) and automation.
• Expert proficiency in SQL with deep knowledge of query optimization, CTEs, and window functions.
• Advanced data visualization skills to deliver executive-level insights in Tableau or Power BI.
• Hands-on experience with Terraform and GitHub Actions for cloud automation.

Physical Demands

• Stand: Occasionally
• Walk: Occasionally
• Sit: Frequently
• Handling / Fingering: Frequently
• Reach Outward: Occasionally
• Reach Above Shoulder: Occasionally
• Climb, Crawl, Kneel, Bend: Occasionally
• Lift / Carry: Occasionally up to 25 lbs
• Push/Pull: Occasionally up to 25 lbs
• See: Constantly
• Taste/ Smell: Not Applicable

Work Environment

• General Office Setting, indoors, temperature controlled

Selection Process

• Live Technical Interview: Shortlisted candidates complete a technical assessment to evaluate SQL and Python skills, Databricks architecture proficiency, and the ability to translate program logic into scalable data models.