Data / Analytics Engineer

In A Nutshell Location: Hybrid Los Angeles, CA, United States Salary: $122,573 - $160,512 / year Job Type: Full-time Experience Level: Mid-level Deadline to apply: July 24, 2026 Serves as the Data & Analytics Engineer for Community Programs (CPs), acting as the Lead Data Architect for CP’s Databricks environment. This role sits at the intersection of data engineering and advanced analytics, responsible for the end-to-end design, implementation, and management of a governed Medallion Architecture (Bronze, Silver, Gold) supporting housing, justice, and clinical operations. This position replaces legacy reporting workflows with a unified, secure data platform that stitches complex, multi‑sector program participation records across disparate systems into a cohesive longitudinal client model. The role bridges infrastructure and advanced analytics by building scalable data products and integrations that support program tracking, executive reporting, and predictive modeling for County and State stakeholders. Responsibilities Build and scale a governed Databricks environment that serves as the single source of truth across housing, justice, and clinical systems Design and implement automated, production-grade data pipelines and CI/CD workflows using Databricks, Terraform, and GitHub Translate complex program logic into scalable data models and reusable data products Build scalable semantic models that map a single client’s journey across disparate housing, justice, and clinical programs, standardizing touchpoints over time. Establish secure-by-design data systems handling sensitive clinical (PHI) and justice (CJI) data utilizing Unity Catalog for centralized governance, audit logging, and access control. Enable advanced analytics by developing curated datasets, APIs, and environments for machine learning and NLP applications Partner with leadership and cross-functional teams to shape how data is used to drive policy, operations, and outcomes Lead and mentor technical staff while setting engineering standards for long-term scalability and maintainability Programmatically map complex, multi-source program utilization (CHAMP, DD, HMIS) to specific funding streams for strict fiscal and grant tracking compliance. Data Infrastructure & Lakehouse Architecture: Design, implement, and maintain a scalable Databricks architecture using Medallion principles. Build and optimize large-scale ETL/ELT pipelines to integrate structured and unstructured data across housing, justice, and clinical systems. Ensure interoperability with healthcare and justice standards (e.g., FHIR, HL7v2) and support a unified, governed data environment serving as the system of record for analytics. Infrastructure Automation & DevOps (CI/CD): Design and manage automated data lifecycles using GitHub Actions and Terraform (Infrastructure as Code). Implement software engineering practices, including version control, automated unit testing, and continuous integration to validate pipeline logic prior to production deployment. Data Modeling & Technical Translation: Design and maintain the Unified Data Model for Community Programs, serving as the foundation for the entire analytical schema. Lead architectural efforts to model and stitch together complex, multi‑sector longitudinal client journeys across CHAMP, DD, HMIS, and various systems. Develop specialized, multi‑dimensional data structures that accurately map cross-program utilization to diverse, overlapping funding streams, enabling precise fiscal, operational, and programmatic evaluation. Data Governance, Security & Compliance: Establish and enforce enterprise data governance frameworks, including RBAC/ABAC, data lineage, audit logging, and data loss prevention. Ensure security, compliance, and data integrity are embedded across all layers of the architecture, supporting high‑trust environments handling regulated data (e.g., PHI, CJI). Analytics Enablement & Data Products: Develop and manage scalable data products, including curated datasets, APIs, and analytical layers that support reporting, dashboards, and advanced analytics. Optimize data access and performance using SQL and modern BI tools (e.g., Tableau, Power BI), enabling consistent, reliable insights for operational and executive decision‑making. Technical Leadership & Delivery Oversight: Provide oversight and mentorship to data engineers, analysts, and scientists, setting engineering standards and promoting best practices in system design. Advanced Analytics Support & Integration: Build and maintain the technical environments required for advanced analytics. Partner with data scientists and DHS Security teams to ensure models and data products are scalable, governed, and aligned with transparency and compliance standards. Skillset Candidates must possess substantial experience in Enterprise Data Architecture, Cloud Infrastructure, and Analytics Engineering. Candidates must hold a relevant degree and demonstrate a proven track record of managing complex data lifecycles within large‑scale Databricks environments. Substantial experience in Cloud Data Engineering and Infrastructure Automation. Preferred: Experience with public sector / healthcare / justice data is a plus Experience working with regulated data (HIPAA, CJIS) is a plus Experience in cross‑agency data integration is a plus Education: Relevant degree from an accredited college or university. Apply Now #J-18808-Ljbffr datadotorg