Principal Data Architect

Jobgether; United States; Hybrid; USD 150.000 - 210.000; Vollzeit

Benefits dieser Stelle

Medical, dental, vision benefits

Hybrid work environment

401(k) contribution

Tuition reimbursement

Professional development allowance

Transportation allowance and parking

Zusammenfassung

Jobgether seeks a seasoned Enterprise Data Architect to define and evolve the organization’s data architecture, models, and standards to support analytics, operations, and AI initiatives. You will guide cloud data platforms and data products, partnering with teams across product, engineering, and data science to deliver scalable, trusted data assets.

You will lead the design of data ingestion, transformation, and governance while ensuring secure access to sensitive information and compliance

Qualifikationen

• 12+ years in data architecture or related tech discipline.
• Experience designing modern cloud data platforms and complex integration architectures.
• Strong knowledge of data modeling (dimensional/relational) and data pipelines.
• Proficient with Snowflake, Databricks, Kafka or equivalent streaming tech, and dbt.
• Strong data governance, metadata management, lineage, privacy, and security.
• Experience architecting data platforms for analytics, operations, and AI/ML use cases.

Aufgaben

• Define and evolve enterprise data architecture, models, integration patterns, standards, and roadmaps.
• Design scalable cloud data platforms, including lakehouse and data warehouse architectures.
• Establish canonical data models and shared business entities for consistent data exchange.
• Develop architecture patterns for ingestion, transformation, orchestration, batch/streaming processing, metadata, lineage, quality, and observability.
• Enable interoperable data products and APIs for applications, analytics, and AI systems.
• Guide integration of healthcare, insurance, employee benefits, claims, eligibility, and provider data.
• Ensure secure, governed access to sensitive information, addressing HIPAA and privacy rules.
• Build AI-ready data foundations supporting ML, generative AI, and intelligent automation.
• Collaborate with product, engineering, analytics, and data science to deliver reusable data products and trusted metrics.
• Advise senior stakeholders; influence architecture decisions; align teams around principles.
• Mentor senior engineers and data architects; promote technical excellence and accountability.

Kenntnisse

Enterprise data architecture

Data modeling

Cloud data platforms

Snowflake

Databricks

Kafka

dbt

Data governance

HIPAA security

Stakeholder communication

Leadership / mentoring

Tools

Snowflake

Databricks

Kafka

dbt

Jobbeschreibung

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.

• Define and evolve enterprise data architecture, data models, integration patterns, technology standards, and long-term technical roadmaps.
• Design resilient, scalable, and cost-effective cloud data platforms, including modern lakehouse and data warehouse architectures.
• Establish canonical data models and shared business entities to ensure consistent definitions and reliable data exchange across systems.
• Develop architecture patterns for data ingestion, transformation, orchestration, batch and streaming processing, metadata management, lineage, quality, and observability.
• Enable interoperable data products and APIs that make trusted information accessible to applications, analytics platforms, and AI systems.
• Guide the integration of complex healthcare, insurance, employee benefits, employer group, claims, eligibility, provider network, and financial data.
• Establish secure, governed access to sensitive information while addressing HIPAA, privacy, security, and other applicable regulatory requirements.
• Build AI-ready data foundations that support machine learning, generative AI, agentic workflows, predictive analytics, and intelligent automation.
• Partner with product, engineering, analytics, and data science teams to deliver reusable data products, trusted metrics, and measurable business outcomes.
• Advise senior technical and business stakeholders, influence architecture decisions, and align teams around shared technical principles.
• 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.

• 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.
• Proven experience designing and implementing modern cloud data platforms and complex data integration architectures.
• Strong knowledge of data modeling, including 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 management, lineage, data quality, access controls, privacy, and security.
• Experience architecting data platforms that support enterprise analytics, operational applications, and AI or machine learning use cases.
• Ability to communicate complex technical concepts clearly, influence senior stakeholders, and build alignment across multiple teams.
• Demonstrated ability to translate architecture strategy into practical implementation and measurable results.
• Strong architectural judgment, strategic thinking, and a hands‑on approach to solving complex technical challenges.

Preferred qualifications:

• Experience in healthcare, health insurance, employee benefits, healthcare technology, or payer and provider ecosystems.
• Familiarity with healthcare interoperability standards and frameworks, including FHIR, HL7, X12, and claims or eligibility data formats.
• Experience managing sensitive healthcare or insurance data in regulated environments, including HIPAA compliance.
• Knowledge of healthcare economics, medical and pharmacy claims, stop‑loss insurance, self‑funded employer health plans, or benefits administration.
• Experience developing governed data products and AI‑ready platforms for advanced analytics and intelligent automation.
• Background in modernizing legacy data ecosystems and integrating information across acquisitions, multiple platforms, or fragmented enterprise systems.
• Authorization to work in the United States without employment visa sponsorship, both currently and in the future.

Benefits:

• Fully paid medical, dental, and vision benefits.
• Flexible paid time off (PTO).
• Company 401(k) contribution.
• Tuition reimbursement.
• Professional development allowance.
• Transportation allowance and daily parking reimbursement.
• Engaging hybrid work environment.