Data Engineer

• Define, own, and execute the enterprise data platform strategy and roadmap
• Lead the transition from legacy EDW architecture to a cloud-native Lakehouse and data engineering platform
• Establish platform success metrics for scalability, reliability, performance, cost management, and business value
• Serve as executive-level authority for enterprise data platform direction and technical decisions
• Lead and develop the Data Platform Engineering team
• Establish role clarity, career pathways, and performance expectations
• Coach and mentor senior technical staff
• Build a sustainable internal delivery model reducing reliance on consultants
• Establish and enforce enterprise standards for data ingestion, transformation, serving layers, medallion and Lakehouse architecture, CI/CD, DevOps, environment management, monitoring, observability, and production support
• Oversee and approve complex architecture and solution designs
• Ensure consistent engineering practices across data domains and delivery teams
• Implement enterprise-wide data quality standards, validation frameworks, and monitoring
• Partner with Security, Compliance, and Governance teams on HIPAA/HITECH, data classification, encryption, access controls, and audit logging
• Maintain accountability for platform stability, incident response, and root-cause remediation
• Provide executive oversight for data domain migrations, analytics and reporting modernization, and legacy EDW decommissioning
• Manage cross-functional dependencies, delivery risks, and modernization sequencing
• Report delivery status, risks, and outcomes to executive leadership
• Liaise between IT leadership, business stakeholders, analytics teams, and external partners
• Translate business and regulatory requirements into scalable technical capabilities
• Communicate platform strategy, risks, progress, and outcomes to executive leadership

Director, Data Platform Engineering

• Design and implement scalable enterprise-wide data architecture
• Optimize data performance and accessibility while ensuring data quality, integrity, and security
• Lead adoption of modern data architecture patterns and cloud-native solutions
• Define future-state data architecture roadmaps aligned with organizational strategy and modernization initiatives
• Develop enterprise data management strategies, including data lake/warehouse implementations, data movement, and data services
• Establish data access patterns, serving layers, semantic models, and APIs for downstream analytics and reporting
• Participate in business analysis activities to elicit data product requirements
• Define reference architectures, coding standards, and reusable patterns for data engineering teams
• Review and approve solution designs for adherence to enterprise data architecture standards
• Provide technical mentorship and design guidance to engineers and analysts
• Participate in the data governance council and contribute to data standards and policies
• Collaborate with security and compliance teams on data classification, encryption, access controls, and audit logging
• Ensure data architectures comply with HIPAA and organizational data privacy standards
• Capture end-user requirements and align technical solutions with strategic business objectives
• Translate business needs into scalable, secure, and well-governed data architecture solutions
• Provide architectural expertise and leadership guidance to data engineering teams

Cloud Data Architect

• Lead complex initiatives with broad impact and participate in large-scale software planning for Identity and Access Management
• Design, develop, and run tooling to discover data and application problems and report issues to engineering and product leadership
• Apply statistical and data science methods to Identity and Access Management business problems
• Serve as a subject matter expert on machine learning, artificial intelligence, and mathematical and statistical techniques for large datasets
• Design, support, and operate data pipelines, data models, dashboards, and API integrations for real-time and batch analytics
• Design and conduct experiments, statistical analyses, and hypothesis testing for controls, policies, and operational processes
• Build AI-powered capabilities to identify inappropriate access, recommend entitlements, and detect anomalous behavior across identity events
• Lead IAM operations, onboarding, initiatives, engineering, line-of-business, and lines-of-defense teams to understand analytical needs and translate them into technical solutions
• Establish and implement engineering and analytical best practices
• Develop solutions according to security, privacy, model risk, and regulatory guidelines
• Develop, test, deploy, and support ML-enabled analytical solutions and guide team adoption of AI/ML and statistical techniques
• Monitor model health, reliability, and drift and ensure remediation
• Use AI-assisted development and analysis tools to accelerate system design, coding, testing, analysis, and troubleshooting
• Validate and integrate AI-assisted outputs while accounting for model limitations, security risks, and operational considerations
• Apply AI responsibly in development and production in alignment with security, compliance, privacy, and ethical standards

Data Engineer jobs in North Carolina

Director, Data Platform Engineering

Cloud Data Architect

Lead Data Engineer – Data Scientist