Enterprise Data Architect

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The Enterprise Data Architect is responsible for defining and governing the target-state enterprise data architecture across operational, analytical, AI/ML, and reporting platforms.

This role partners with business, engineering, security, and governance stakeholders to establish scalable data patterns, trusted data products, AI-ready data foundations, and resilient data operations that support underwriting, claims, finance, risk aggregation, regulatory reporting, and enterprise analytics.

The role will provide architecture leadership across cloud-native data platforms, integration patterns, data governance, DataOps/MLOps, and engineering standards.

The architect will ensure solutions are secure, compliant, observable, automated, reusable, and aligned to enterprise architecture guardrails and insurance industry expectations.

Key Accountabilities/Deliverables:


* Define the enterprise data architecture strategy, reference patterns, roadmap, and standards across data ingestion, transformation, storage, consumption, AI/ML, and operational reporting capabilities.


* Establish target-state architectures for data platforms including Lakehouse, data warehouse, semantic layer, data mesh/domain-aligned data products, master/reference data, metadata, lineage, cataloging, and data quality management.


* Partner with business and technology leaders to translate underwriting, claims, finance, actuarial, risk, and regulatory needs into governed data capabilities and reusable engineering patterns.


* Design and govern AI-ready data foundations including governed feature stores, vector/embedding patterns, model training and inference data pipelines, retrieval-augmented generation grounding, and responsible AI controls.


* Lead architecture reviews for data and analytics initiatives, ensuring alignment to security, privacy, regulatory, data classification, retention, least privilege, segregation of duties, and audit readiness requirements.


* Define DataOps, MLOps, and engineering requirements for CI/CD, automated testing, data quality gates, policy-as-code, infrastructure-as-code, environment promotion, rollback, monitoring, and release controls.


* Create architecture blueprints, solution decision records, integration patterns, data flow diagrams, domain models, canonical data contracts, and reusable implementation playbooks for engineering teams.


* Guide modernization of legacy data assets and reporting solutions into cloud-native, secure, scalable, and cost-optimized platforms aligned to Azure-first enterprise direction with limited AWS workloads where appropriate.


* Support vendor/platform evaluations using build vs.

buy vs.

extend analysis, ensuring selections align to enterprise architecture, integration, security, compliance, extensibility, and total cost of ownership.


* Partner with cybersecurity and platform teams to implement Zero Trust data access, network segmentation, encryption, key management, priv...