Full Stack, Data & Analytics Engineer

SCAN Health Insurance•Long Beach, CA

1d•Hybrid

About The Position

Serve as a full-stack data and analytics engineer within a business-aligned scrum team. This role designs, develops, and delivers end-to-end solutions—including data pipelines, models, semantic layers, and visualizations—while playing a hands-on role in enabling AI/ML use cases. In this role you will ensure that data is analytics and AI-ready, support data and feature engineering, and collaborate closely with report developers, data scientists, and AI engineers to bring predictive and prescriptive analytics, as well as generative AI solutions, into production. Deep familiarity with healthcare data and Medicare Advantage business processes is essential.

Requirements

Bachelor's degree in Computer Science, Data Analytics, or related field (or equivalent experience).
Hands-on experience delivering BI and reporting solutions (Power BI, Tableau, or similar) that translate data and AI-driven insights into actionable business decisions
3–6 years in data engineering, analytics engineering, or applied ML/AI, ideally in a business-aligned role delivering end-user solutions
Experience building semantic models and defining governed metrics
Strong SQL and experience with cloud analytics platforms such as Snowflake, Databricks, or similar.
Hands-on experience with ETL/ELT tools (Azure Data Factory, Coalesce, dbt, or similar).
Strong familiarity with Medicare Advantage domains (e.g., claims, enrollment, provider data, risk adjustment, Stars/quality, etc.)
Experience building ML-ready datasets and supporting data scientists in training and inference workflows.
Familiarity with LLM/NLP use cases (RAG, embeddings, vector stores)
Proficiency in Python for data engineering and light ML workflows (Pandas, PySpark, scikit-learn, or similar).
Experience working in agile delivery frameworks (Scrum/SAFe) with rapid iteration in business-facing teams.
Familiarity with agile delivery methods (Scrum/SAFe) and software (e.g. Azure DevOps, JIRA, etc).
Healthcare & Medicare Advantage expertise: Understands health plan data domains (claims, provider, member, risk adjustment, quality) and how analytics/AI/ML can improve outcomes
AI/ML Enablement: Comfortable working side-by-side with data scientists and ML engineers to ensure models are production-ready, performant, and aligned to healthcare business needs
Full-stack mindset: Ability to span the data lifecycle—back-end pipelines, semantic models, and front-end dashboards—integrating AI insights along the way
Business acumen: Connects technical work to strategic health plan objectives, such as Stars improvement, member engagement, and cost management
Problem solving: Resourceful in handling structured and unstructured healthcare data, able to design innovative solutions for AI/ML pipelines
Clear communicator: Can explain technical concepts to non-technical users and partner across business and technology groups
Mentorship: Serves as a mentor to help elevate BI/analytics colleagues in best practices for data engineering and AI enablement as well as delivering business value via data and analytics
Adaptability: Learns emerging AI/ML tools and healthcare regulations quickly and applies them responsibly in production environments

Responsibilities

Collaborate with business stakeholders across the health plan to translate business needs into actionable analytic, BI, and AI-enabled solutions that deliver measurable value
Build and refine analytics-ready data sets needed for dashboards, models, and GenAI applications
Perform hands-on feature engineering and create ML-ready datasets to accelerate model development across health plan priorities such as member experience, operational efficiency, and/or clinical excellence
Implement and support AI/ML workflows such as RAG, NLP pipelines, Cortex functions, embeddings, and predictive models
Guide development of, and help maintain, semantic layers and governed metric definitions used across BI dashboards, operational reporting, and AI/ML pipelines
Build business-facing dashboards and lightweight data-as-a-service applications (Power BI, Streamlit, or similar) that embed predictive, prescriptive, or generative insights for decision-makers
Collaborate with data scientists and AI engineers to operationalize models—ensuring datasets, features, and inference pipelines are versioned, monitored, and production-ready
Apply responsible data practices by embedding lineage, quality checks, PHI/PII protection, and responsible AI guardrails directly into your workflows
Identify and resolve data quality issues that impact business outcomes and proactively recommend data improvements to accelerate delivery of use cases
Continuously explore new AI/ML capabilities, particularly LLM- or agentic- driven workflows, and integrate them into business-facing solutions where appropriate
Actively support the achievement of SCAN’s Vision and Goals.
Other duties as assigned.

Benefits

Base Salary Range: $92,400 to $159,133 annually
An annual employee bonus program
Robust Wellness Program
Generous paid-time-off (PTO)
11 paid holidays per year, 1 floating holiday, birthday off, and 2 volunteer days
Excellent 401(k) Retirement Saving Plan with employer match
Robust employee recognition program
Tuition reimbursement
An opportunity to become part of a team that makes a difference to our members and our community every day!
A competitive compensation and benefits program
An annual employee bonus program
Generous paid-time-off (PTO)
Eleven paid holidays per year
Excellent Retirement Savings program
A work-life balance
An opportunity to become part of a team that makes a difference to our members and our community every day!