Alignment Health is breaking the mold in conventional health care, committed to serving seniors and those who need it most: the chronically ill and frail. It takes an entire team of passionate and caring people, united in our mission to put the senior first. We have built a team of talented and experienced people who are passionate about transforming the lives of the seniors we serve. In this fast-growing company, you will find ample room for growth and innovation alongside the Alignment Health community. Working at Alignment Health provides an opportunity to do work that really matters, not only changing lives but saving them. Together.

The Enterprise Data Architect designs and implements our AVA data strategy and architecture ensuring data is accessible, reliable (quality), and aligned with business needs focusing on data integration, governance, and compliance. Enterprise data architect provides expert support across the AVA enterprise information data model; data intake, data transformation, data quality, metadata and master data management, data virtual-ization, data services and consumption.

Enterprise Data Strategy & Architecture

Develop, maintain and scale AVA’s enterprise data architecture strategy, aligning with long-term business objectives, regulatory environments, and innovation priorities.
Establish blueprints for hybrid data ecosystems that span operational systems, enterprise data warehouses, cloud-native platforms, and edge compute environments.
Define reference architectures and reusable design patterns that support both legacy and cloud-native data application.
Develop and implement enterprise-wide data architecture standards, policies, and best practices.

AI & Machine Learning Enablement

Architect AI/ML-ready data pipelines, including real-time streaming, feature engineering, and data annotation processes.
Collaborate with AI/ML teams to ensure model readiness, scalability, and compliance—including support for supervised, unsupervised, and generative learning systems to improve data accessibility, usability and adoption.
Design systems to support domain-specific LLMs, chat-based AI assistants, and intelligent document processing tools.
Define data architectures that support synthetic data generation, model validation, and the use of third-party foundation models via secure APIs.

Generative AI & Intelligent Automation

Identify opportunities to embed generative AI into clinical, operational, and member-facing workflows, including summarization, co-piloting, and content generation.
Guide adoption of low-code/no-code tools that empower business users to use data, build logic, or co-create automation with minimal technical friction.
Collaborate with HR, Ops, and L&D leaders to design systems that support knowledge management, intelligent upskilling, and augmented workforce tools.

Data Modeling, Integration & Virtualization

Lead the design and implementation of data models (conceptual, logical, physical) supporting operational reporting, advanced analytics, and AI initiatives.
Oversee the integration of structured and unstructured data from internal systems, APIs, EHRs, claims, devices, and external sources.
Champion data virtualization where appropriate to reduce redundancy and accelerate access to timely insights.
Drive adoption of modern cloud-based data solutions, ensuring performance, security, and compliance.

Governance, Quality, and Compliance

Develop and enforce enterprise data governance frameworks in coordination with compliance, security, and risk teams.
Build data stewardship programs and implement tools to maintain high standards in data lineage, accuracy, completeness, and freshness.
Ensure that data used for AI is explainable, secure, and aligned with enterprise ethical AI standards, including privacy and fairness.

Collaboration & Cross-Functional Leadership

Serve as a senior data thought partner to leaders across clinical operations, population health, product, innovation, finance, and compliance.
Work closely with business leaders, IT teams, and stakeholders to align data initiatives with business goals.
Partner with the Chief Data & Analytics Officer (CDAO), VP of AI/ML, and Product Engineering to define enterprise-wide AI adoption roadmaps. [AW: Who is, will be the CDAO?]
Mentor junior architects and analysts in modern data architecture principles, engineering best practices, and AI design patterns.

Experience Requirements:

Minimum 10 years of progressive experience in data architecture, enterprise data integration, and database design.
Minimum 2 years of experience working in a health plan, payer, or healthcare delivery system, including familiarity with claims data, EHRs, HEDIS, CMS, and HIPAA.
Demonstrated experience leading AI- or ML-focused architecture initiatives, ideally in healthcare, fintech, or another regulated environment.

Educational Requirements:

Required: Bachelors degree in Computer Science, Engineering, Data Science, Statistics, Mathematics, or a related field.
Preferred: Master’s degree, MBA, or Ph.D. in the above areas with specialization in data strategy, AI/ML, or systems design.

Specialized Technical Skills:

Advanced knowledge of:

Data modeling tools and methodologies (e.g., Kimball, Inmon, Data Vault)
Cloud data platforms (e.g., Snowflake, BigQuery, Redshift, Databricks)
Data integration and orchestration (e.g., Informatica, Talend, dbt, Airflow)
ML and LLM-enabling infrastructure (e.g., MLflow, Feature Store, HuggingFace, LangChain, vector DBs)
Hands-on experience with:
Generative AI APIs (e.g., OpenAI, Anthropic, Cohere) and model hosting
NLP, embeddings, and prompt engineering strategies
Secure API design and federated learning concepts
Certifications such as TOGAF, DAMA-CDMP, AWS Certified Data Analytics, or similar are preferred.

Core Competencies:

Visionary thinker with strong systems design intuition.
Confident communicator with the ability to bridge technical depth and executive-level influence.
Values innovation, inclusion, and ethical technology design.
Proven ability to lead through ambiguity in fast-paced environments.

Licensure/Certifications (Preferred):

TOGAF, DAMA, AWS Certified Big Data/Analytics, Google Cloud Professional Data Engineer, ITIL, SAP, CEA, or MDM certifications.

Physical Requirements:

Regularly required to sit, stand, walk, speak, and use a computer.
Must be able to lift or move items up to 10 pounds.
Specific vision requirements include close vision and the ability to adjust focus.

Pay Range: $227,952.00 - $341,928.00

Alignment Health is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, age, protected veteran status, gender identity, or sexual orientation.

*DISCLAIMER: Please beware of recruitment phishing scams affecting Alignment Health and other employers where individuals receive fraudulent employment-related offers in exchange for money or other sensitive personal information. Please be advised that Alignment Health and its subsidiaries will never ask you for a credit card, send you a check, or ask you for any type of payment as part of consideration for employment with our company. If you feel that you have been the victim of a scam such as this, please report the incident to the Federal Trade Commission at https://reportfraud.ftc.gov/#/. If you would like to verify the legitimacy of an email sent by or on behalf of Alignment Health’s talent acquisition team, please email careers@ahcusa.com.