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Stellus Rx

Trusted, pharmacist-led health support in every moment that matters.

Senior Data Architect

Data EngineerData EngineerFull TimeRemoteSeniorTeam 201-500Since 2022H1B No SponsorCompany SiteLinkedIn

Location

Peru

Posted

94 days ago

Salary

$52K / year

Seniority

Senior

Job Description

Senior Data Architect

Stellus Rx

• 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. • Use AI-assisted modeling tools to accelerate data model design, evaluate architectural trade-offs, and validate designs against business requirements before committing to implementation. • 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. • Establish data ontology, taxonomy, and semantic layer standards that enable AI systems to reason over organizational data accurately and consistently. • 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. • Design scalable data models and ELT/ETL pipeline architectures that support both traditional analytics and AI/ML model training and inference workloads. • 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. • Define standards for data partitioning, indexing, caching, and storage optimization; use AI-driven performance analysis to continuously validate and improve architectural decisions. • Partner with Data Engineers to translate architectural blueprints into production-ready pipelines, providing hands-on guidance and AI-augmented design reviews. • 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. • 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. • Develop and maintain a master data management (MDM) strategy that ensures consistency, accuracy, and trustworthiness of critical data assets across systems. • Champion data privacy and security principles in architectural design, including data lineage tracking, access controls, and anonymization strategies for sensitive healthcare data. • 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. • 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. • 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. • Partner with Business Intelligence and Product teams to ensure the data architecture supports self-service analytics, real-time dashboards, and AI-powered reporting capabilities. • 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. • Mentor Data Engineers and Analysts, guiding them in applying architectural standards and AI-augmented data development practices. • Communicate architectural decisions, trade-offs, and roadmap recommendations clearly to both technical teams and executive leadership. • Stay current on emerging data technologies, AI/ML data infrastructure trends, and industry best practices; provide recommendations on adoption timing and implementation approach.

Job Requirements

  • 7+ years of experience in data architecture, data engineering, or a closely related field.
  • 3+ years of experience designing enterprise-scale data platforms in cloud environments (AWS strongly preferred).
  • 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.
  • Deep expertise in data modeling techniques including dimensional modeling, data vault, and lakehouse patterns.
  • Strong knowledge of ELT/ETL pipeline architecture and workflow orchestration (Airflow or similar).
  • Experience with cloud data platforms such as AWS Redshift, S3, Glue, Athena, or equivalents.
  • Proficiency in SQL and at least one scripting language (Python preferred).
  • Experience with relational and NoSQL databases; familiarity with vector databases a plus.
  • Strong understanding of data governance, data quality frameworks, and MDM principles.
  • Familiarity with healthcare data compliance requirements (HIPAA, SOC 2).
  • Excellent communication skills with the ability to convey complex architectural concepts to technical and non-technical audiences.
  • Bachelor's or graduate degree in Computer Science, Information Systems, Statistics, or a related quantitative field.
  • High English proficiency, written and verbal.

Benefits

  • Health insurance
  • Professional development opportunities

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