Data Engineer

• Define the enterprise data architecture strategy, reference patterns, roadmap, and standards across ingestion, transformation, storage, consumption, AI/ML, and operational reporting
• Establish target-state architectures for Lakehouse, data warehouse, semantic layer, data mesh/domain-aligned data products, master/reference data, metadata, lineage, cataloging, and data quality management
• 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 feature stores, vector/embedding patterns, model training and inference pipelines, RAG grounding, and responsible AI controls
• Lead architecture reviews for data and analytics initiatives, ensuring security, privacy, regulatory, classification, retention, least privilege, segregation of duties, and audit readiness
• Define DataOps, MLOps, and engineering requirements for CI/CD, 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 implementation playbooks
• Guide modernization of legacy data assets and reporting solutions into secure, scalable, cost-optimized cloud-native platforms aligned to Azure-first direction
• Support vendor and platform evaluations through build-vs-buy-vs-extend analysis
• Partner with cybersecurity and platform teams on Zero Trust access, network segmentation, encryption, key management, privileged access, and secure data sharing
• Define observability standards for pipelines, data products, models, SLAs/SLOs, lineage, incident response, DR/BCP, capacity, cost management, and service health reporting
• Perform other duties as assigned

Enterprise Data Architect

• Own ClickHouse schema, data model, and migrations
• Own materialized views, performance, and scale
• Own data ingestion, lifecycle, and operability
• Build reports and analytics via Metabase
• Enable data storytelling
• Provide world-class data storage, reporting, analytics, and visualization capabilities
• Build automations, Claude configurations, test harnesses, and documentation so humans and AI can contribute safely
• Set technical conventions and make pragmatic depth-versus-breadth decisions
• Work across SQL, Go, Python, Helm, and potentially TypeScript
• Materialize, report, and scale security-posture data correctly without owning connectors, discovery, detection, classification, risk scoring, PostgreSQL, or core application services

Data Engineer jobs in Ohio

Enterprise Data Architect

Staff Data Engineer