• Be the hands-on technical lead for dashboard, reporting, and data engineering work within a large-scale Medicaid EDW and analytics program. • Design, develop, and maintain enterprise-level dashboards and reports using Tableau and Python-based frameworks, ensuring they're performant, reusable, and built to last. • Build and optimize scalable data processing pipelines using Python, supporting both ongoing analytics needs and federal reporting requirements. • Write and tune SQL and stored procedures across relational platforms — primarily Teradata — with a focus on accuracy and efficiency at enterprise scale. • Support Medicaid analytics and federal reporting initiatives including T-MSIS, PERM, MARS, and Quality of Care programs, working closely with SMEs and compliance teams. • Participate in cloud migration and modernization work within Azure-based architectures, contributing to the shift from legacy systems toward modern platforms. • Collaborate with analysts, QA teams, and BI reporting leads to validate data quality, resolve discrepancies, and ensure timely delivery of reporting deliverables. • Support production operations — including incident response and root-cause analysis — and contribute to a stable, reliable analytics environment. • Participate in code reviews, maintain source control hygiene, and work within CI/CD processes using Azure DevOps and GitHub.

• Design and develop high-performance, scalable backend systems using PHP • Lead architecture decisions and drive best practices across the engineering team • Refactor and modernize legacy systems into maintainable, modular services • Build and optimize RESTful APIs • Work closely with product, QA, and support teams to deliver high-quality features • Troubleshoot and resolve complex production issues with a focus on reliability and performance • Mentor junior developers and contribute to engineering excellence • Improve CI/CD pipelines, code quality, and deployment processes

• Build and maintain production Python APIs (FastAPI or similar) • Design and run data pipelines (ETL, ingestion, transformation) • Own data quality — validation, monitoring, failure handling • Structure data for RAG systems and AI agents • Design and manage databases (PostgreSQL + vector DBs) • Integrate external systems (APIs, webhooks, third-party tools)

• Operate autonomously to generate precise 3D assets and programmed outputs. • Writing Blender Python (bpy) scripts or Three.js/JavaScript code for 3D geometry. • Producing collision-accurate meshes from 2D reference images. • Producing programmatic JSON/JS outputs representing the mesh and maintaining trajectory logs. • Auditing all assets against strict quality checklists before submission.