Senior Data Architect

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    "description": "<p><span style=\"font-weight: bold\">Job Summary</span></p>\n<p>We're opening eyes, hearts and minds to the impact that a pharmacy team can have in changing lives.</p>\n<p> </p>\n<p>Join our group of talented, committed team members-pharmacists, pharmacy care coordinators, technologists, product strategists and more-to create and expand the delivery of personalized health support that people didn't even know could be possible.</p>\n<p><br></p>\n<p>The <span style=\"font-weight: bold\">Senior Data Architect</span> for Stellus Rx will be a key member of our <span style=\"font-weight: bold\">Technology Team</span>, working closely with Stellus Rx leaders and across the organization to unlock the health of millions of Americans. We are a culture that is unabashedly driven by purpose — making a difference to patients and team members while growing at an accelerated rate.</p>\n<p><br></p>\n<p>This role is built for a data architect who actively uses AI to design smarter data systems, accelerate architectural decision-making, and build the data foundations that enable AI and machine learning to thrive across the organization — rather than treating AI as an afterthought in the data stack.</p>\n<p><br></p>\n<p><span style=\"font-weight: bold\">Role and Responsibilities:</span></p>\n<p><span style=\"font-weight: bold\">AI-Informed Data Architecture Design</span></p>\n<ul>\n<li>Define and maintain enterprise data architecture standards across structured, semi-structured, and unstructured data domains — with deliberate design for AI/ML workloads, including feature stores, vector databases, and embedding pipelines.</li>\n<li>Use AI-assisted modeling tools to accelerate data model design, evaluate architectural trade-offs, and validate designs against business requirements before committing to implementation.</li>\n<li>Design and govern the organization's cloud data lake, data warehouse, and lakehouse architectures on AWS — ensuring they are optimized for both analytical and AI/ML consumption patterns.</li>\n<li>Establish data ontology, taxonomy, and semantic layer standards that enable AI systems to reason over organizational data accurately and consistently.</li>\n<li>Evaluate emerging data architecture patterns — including retrieval-augmented generation (RAG), real-time feature serving, and vector search — and build a roadmap for their adoption across Stellus Rx.</li>\n</ul>\n<p><br></p>\n<p><span style=\"font-weight: bold\">AI-Ready Data Modeling &amp; Pipeline Architecture</span></p>\n<ul>\n<li>Design scalable data models and ELT/ETL pipeline architectures that support both traditional analytics and AI/ML model training and inference workloads.</li>\n<li>Use AI code generation tools to accelerate the authoring and validation of data models, transformation logic, and pipeline configurations — replacing manual, repetitive design work with intelligent, AI-assisted development.</li>\n<li>Define standards for data partitioning, indexing, caching, and storage optimization; use AI-driven performance analysis to continuously validate and improve architectural decisions.</li>\n<li>Partner with Data Engineers to translate architectural blueprints into production-ready pipelines, providing hands-on guidance and AI-augmented design reviews.</li>\n</ul>\n<p><br></p>\n<p><span style=\"font-weight: bold\">Data Governance, Quality &amp; Compliance</span></p>\n<ul>\n<li>Define and enforce data governance frameworks, data quality standards, and data contracts across the enterprise — using AI-powered data observability tools to automate quality monitoring and surface issues proactively rather than through manual review.</li>\n</ul>\n<ul>\n<li>Ensure data architecture meets compliance requirements relevant to healthcare (HIPAA, SOC 2, NIST); use AI-assisted compliance tooling to continuously monitor for policy drift and streamline audit evidence generation.</li>\n<li>Develop and maintain a master data management (MDM) strategy that ensures consistency, accuracy, and trustworthiness of critical data assets across systems.</li>\n<li>Champion data privacy and security principles in architectural design, including data lineage tracking, access controls, and anonymization strategies for sensitive healthcare data.</li>\n</ul>\n<p><br></p>\n<p><span style=\"font-weight: bold\">AI &amp; Analytics Enablement</span></p>\n<ul>\n<li>Design data infrastructure that serves as the foundation for AI/ML initiatives — ensuring data is accessible, well-labeled, versioned, and structured to support model training, validation, and ongoing inference at scale.</li>\n<li>Collaborate with data scientists and ML engineers to understand modeling requirements and translate them into data architecture decisions that reduce friction in the AI development lifecycle.</li>\n<li>Use AI-assisted analysis to identify high-value data assets that are underutilized, and develop strategies to unlock their potential for analytics and AI-driven decision-making.</li>\n<li>Partner with Business Intelligence and Product teams to ensure the data architecture supports self-service analytics, real-time dashboards, and AI-powered reporting capabilities.</li>\n</ul>\n<p><br></p>\n<p><span style=\"font-weight: bold\">Standards, Documentation &amp; Team Enablement</span></p>\n<ul>\n<li>Define and maintain data architecture standards, patterns, and best practices across the organization; use AI tools to generate, review, and keep documentation current with minimal manual overhead.</li>\n<li>Mentor Data Engineers and Analysts, guiding them in applying architectural standards and AI-augmented data development practices.</li>\n<li>Communicate architectural decisions, trade-offs, and roadmap recommendations clearly to both technical teams and executive leadership.</li>\n<li>Stay current on emerging data technologies, AI/ML data infrastructure trends, and industry best practices; provide recommendations on adoption timing and implementation approach.</li>\n</ul>\n<p><br></p>\n<p><span style=\"font-weight: bold\">Qualifications and Requirements:</span></p>\n<ul>\n<li>7+ years of experience in data architecture, data engineering, or a closely related field.</li>\n<li>3+ years of experience designing enterprise-scale data platforms in cloud environments (AWS strongly preferred).</li>\n<li>Required: Demonstrated, hands-on experience using AI tools to accelerate data architecture design, automate data quality, or enable AI/ML workloads — with specific examples you can speak to.</li>\n<li>Deep expertise in data modeling techniques including dimensional modeling, data vault, and lakehouse patterns.</li>\n<li>Strong knowledge of ELT/ETL pipeline architecture and workflow orchestration (Airflow or similar).</li>\n<li>Experience with cloud data platforms such as AWS Redshift, S3, Glue, Athena, or equivalents.</li>\n<li>Proficiency in SQL and at least one scripting language (Python preferred).</li>\n<li>Experience with relational and NoSQL databases; familiarity with vector databases a plus.</li>\n<li>Strong understanding of data governance, data quality frameworks, and MDM principles.</li>\n<li>Familiarity with healthcare data compliance requirements (HIPAA, SOC 2).</li>\n<li>Excellent communication skills with the ability to convey complex architectural concepts to technical and non-technical audiences.</li>\n<li>Bachelor's or graduate degree in Computer Science, Information Systems, Statistics, or a related quantitative field.</li>\n<li>High English proficiency, written and verbal.</li>\n</ul>\n<p> </p>\n<p><span style=\"font-weight: bold\">Preferred Experience:</span></p>\n<ul>\n<li>Hands-on experience designing data infrastructure for AI/ML workloads, including feature stores, vector databases, or RAG pipelines.</li>\n<li>Familiarity with AI-powered data observability platforms (e.g., Monte Carlo, Soda, or similar).</li>\n<li>Experience with healthcare data standards including FHIR and HL7.</li>\n<li>Experience with real-time streaming architectures (Kafka, Kinesis, or similar).</li>\n<li>Relevant certifications: AWS Certified Data Analytics, AWS Solutions Architect, or DAMA CDMP.</li>\n<li>Bilingual — Spanish and English.</li>\n<li>MBA or advanced degree.</li>\n</ul>",
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