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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Data Architect - **Company:** PARETO HEALTH, INC. - **Location:** Philadelphia, PA, United States - **Contract:** Permanent contract - **Skills:** Training Data, Application Programming Interfaces (APIs), Artificial Intelligence, Business Analytics Applications, Data Analysis, ASC X12 Standards, Data Architecture, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Dataspaces, Data Systems, Distributed Computing Environment, Electronic Data Interchange (EDI), Machine Learning, Metadata, Meta-Data Management, Cloud Services, Data Streaming, Data Ingestion, Fast Healthcare Interoperability Resources, System Availability, Snowflake, Generative AI, Agentic-AI, Data Analytics, Health Level Seven International, Apache Kafka, Operational Systems, Data Management, Video Streaming, Stream Processing, Data Pipelines, Databricks - **Published:** October 26, 2026 - **Apply:** https://www.phillyjobs.com/job.asp?id=3472467946&tx=CT3836THI&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role * 12+ years of experience in data architecture, data engineering, data platforms, or related technical disciplines, with demonstrated experience leading enterprise-scale architecture. * Proven track record designing and implementing modern cloud data platforms and complex data integration architectures. * Strong expertise in data modeling, dimensional and relational modeling, distributed data processing, data pipelines, and data platform design. * Experience with modern data technologies such as Snowflake, Databricks, cloud-native data services, Kafka or equivalent streaming technologies, dbt, and contemporary orchestration tools. * Strong understanding of data governance, metadata, lineage, data quality, access controls, privacy, and security. * Experience architecting data platforms that support enterprise analytics, operational applications, and AI/ML use cases. * Ability to communicate complex technical concepts clearly and influence senior technical and business stakeholders. * Demonstrated ability to move from architecture strategy to practical implementation and measurable outcomes., * Experience in healthcare, health insurance, employee benefits, healthcare technology, or payer/provider ecosystems. * Familiarity with healthcare data standards and interoperability frameworks such as FHIR, HL7, X12, and relevant claims and eligibility data formats. * Experience working with sensitive healthcare or insurance data in regulated environments, including HIPAA compliance requirements. * Knowledge of healthcare economics, medical and pharmacy claims, stop-loss insurance, self-funded employer health plans, or benefits administration. * Experience building governed data products and AI-ready platforms that enable advanced analytics and intelligent automation. * Experience modernizing legacy data ecosystems and integrating data across acquisitions, multiple platforms, or fragmented enterprise systems. ## Description As Principal Data Architect, you will define and drive the enterprise data architecture strategy across ParetoHealth, enabling trusted, connected, secure, and AI-ready data products that power business intelligence, advanced analytics, and intelligent automation. You will work across business, product, engineering, analytics, and AI teams to translate complex business needs into scalable data platforms and architectures. You will bring deep expertise in modern data architecture, strong technical judgment, and the ability to navigate complex data ecosystems, ideally within healthcare, health insurance, employee benefits, or financial services. This is a hands-on architecture leadership role for someone who can think strategically, influence across the organization, and drive implementation from vision to execution. Key Responsbilities: Enterprise Data Architecture & Strategy * Define and evolve the enterprise data architecture, data models, integration patterns, and technology standards to support ParetoHealth's business and technology strategy. * Design scalable, resilient, and cost-effective data architectures across operational systems, analytical platforms, and data products. * Establish canonical data models and shared business entities across domains, enabling consistent definitions and reliable data exchange. * Drive architectural decisions that balance immediate business needs with long-term scalability, flexibility, and maintainability. Modern Data Platforms & Engineering * Architect modern cloud-based data platforms and lakehouse or warehouse solutions that support batch, streaming, and near-real-time data processing. * Establish patterns for data ingestion, transformation, orchestration, data quality, metadata management, lineage, and observability. * Enable interoperable data products and APIs that make trusted data accessible to applications, analytics, and AI systems. * Partner with engineering teams to establish best practices for data modeling, platform reliability, performance, security, and cost optimization. Healthcare & Insurance Data * Design data architectures that integrate complex, fragmented data across healthcare, health insurance, employee benefits, employer groups, claims, eligibility, provider networks, and financial systems, as applicable. * Develop a strong understanding of healthcare benefits and insurance business processes, data entities, and industry-specific interoperability requirements. * Enable secure and governed access to sensitive healthcare and personally identifiable information, incorporating HIPAA and other applicable regulatory and privacy requirements. * Translate complex healthcare and insurance data into consistent, usable models that support business operations, financial analysis, cost transparency, and better decision-making. AI, Analytics & Data Products * Build an AI-ready data foundation that enables machine learning, generative AI, agentic workflows, and intelligent automation. * Define architectures for high-quality, contextual, discoverable, and governed data that can be safely consumed by AI applications. * Partner with data science, analytics, product, and engineering teams to enable predictive insights, operational intelligence, and data-driven product innovation. * Establish data product principles that emphasize business ownership, trusted metrics, reusability, and measurable business outcomes. Technical Leadership & Governance * Serve as a trusted technical advisor to engineering, product, business, security, and executive stakeholders. * Define architectural standards, reference architectures, design principles, and technical roadmaps. * Drive alignment across teams and influence decisions without relying solely on formal authority. * Mentor senior engineers and data architects, raise the bar for technical excellence, and foster a culture of accountability and continuous improvement.