Principal Data Architect

Accountabilities: You will define and implement enterprise data architecture that supports business priorities, operational efficiency, analytics, and long-term technology evolution. You will guide technical teams toward scalable, secure, and cost-effective solutions while establishing standards that improve data quality, interoperability, and reuse.

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Define and evolve enterprise data architecture, data models, integration patterns, technology standards, and long-term technical roadmaps.

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Design resilient, scalable, and cost-effective cloud data platforms, including modern lakehouse and data warehouse architectures.

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Establish canonical data models and shared business entities to ensure consistent definitions and reliable data exchange across systems.

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Develop architecture patterns for data ingestion, transformation, orchestration, batch and streaming processing, metadata management, lineage, quality, and observability.

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Enable interoperable data products and APIs that make trusted information accessible to applications, analytics platforms, and AI systems.

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Guide the integration of complex healthcare, insurance, employee benefits, employer group, claims, eligibility, provider network, and financial data.

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Establish secure, governed access to sensitive information while addressing HIPAA, privacy, security, and other applicable regulatory requirements.

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Build AI-ready data foundations that support machine learning, generative AI, agentic workflows, predictive analytics, and intelligent automation.

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Partner with product, engineering, analytics, and data science teams to deliver reusable data products, trusted metrics, and measurable business outcomes.

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Advise senior technical and business stakeholders, influence architecture decisions, and align teams around shared technical principles.

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Mentor senior engineers and data architects, promote technical excellence, and encourage accountability and continuous improvement.

Requirements:

You will bring extensive experience in enterprise data architecture and modern data platforms, along with the technical judgment needed to translate complex business challenges into practical solutions. You should be comfortable balancing long-term architectural strategy with hands-on implementation and communicating effectively with both technical and nontechnical stakeholders.

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At least 12 years of experience in data architecture, data engineering, data platforms, or a related technical discipline, including leadership of enterprise-scale architecture initiatives.

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Proven experience designing and implementing modern cloud data platforms and complex data integration architectures.

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Strong knowledge of data modeling, including dimensional and relational modeling, distributed data processing, data pipelines, and data platform design.

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Experience with modern data technologies such as Snowflake, Databricks, cloud-native data services, Kafka or equivalent streaming technologies, dbt, and contemporary orchestration tools.

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Strong understanding of data governance, metadata management, lineage, data quality, access controls, privacy, and security.

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Experience architecting data platforms that support enterprise analytics, operational applications, and AI or machine learning use cases.

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Ability to communicate complex technical concepts clearly, influence senior stakeholders, and build alignment across multiple teams.

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Demonstrated ability to translate architecture strategy into practical implementation and measurable results.

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Strong architectural judgment, strategic thinking, and a hands-on approach to solving complex technical challenges.

Preferred qualifications:

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Experience in healthcare, health insurance, employee benefits, healthcare technology, or payer and provider ecosystems.

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Familiarity with healthcare interoperability standards and frameworks, including FHIR, HL7, X12, and claims or eligibility data formats.

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Experience managing sensitive healthcare or insurance data in regulated environments, including HIPAA compliance.

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Knowledge of healthcare economics, medical and pharmacy claims, stop-loss insurance, self-funded employer health plans, or benefits administration.

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Experience developing governed data products and AI-ready platforms for advanced analytics and intelligent automation.

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Background in modernizing legacy data ecosystems and integrating information across acquisitions, multiple platforms, or fragmented enterprise systems.

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Authorization to work in the United States without employment visa sponsorship, both currently and in the future.

Benefits:

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Fully paid medical, dental, and vision benefits.

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Flexible paid time off (PTO).

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Company 401(k) contribution.

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Tuition reimbursement.

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Professional development allowance.

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Transportation allowance and daily parking reimbursement.

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Engaging hybrid work environment. How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether?    Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.     #LI-CL1