IT Principal Data Architect - Data Migration, OLTP, ETL

Essential Duties and Responsibilities

• Determine optimal architecture to support business requirements and solve highly complex technical challenges.
• Stay current with industry trends/development and contribute to ongoing research and development.
• Guide and mentor architects and engineers establishing and maintaining architecture of highly complex solutions.
• Produce solution architecture and estimates to support initiative proposals and business development.
• Contribute to standards and approaches for architecture of enterprise data solutions.
• Optimize overall data/information flow by reducing redundancy and enabling accessibility within security boundaries.
• Identify data-related business requirements and service standards, and translate these into actionable architecture design.
• Frequently responsible for providing guidance, coaching, and training to other employees across the organization within area of expertise.

• Own the end-to-end technical architecture for complex data migration initiatives from legacy systems to modern data platforms.
• Define target-state data architectures including modern applications, data lakes, warehouses, lakehouse patterns, and real-time/streaming integrations.
• Design migration strategies (phased, domain-based, parallel run, cutover) based on data criticality, volume, and business risk.
• Ensure alignment with enterprise data architecture, integration standards, and cloud platform strategies.

• Lead hands-on technical design and delivery of data ingestion, transformation, and persistence layers.
• Establish standards for ETL/ELT pipelines, orchestration, schema management, metadata, and error handling.
• Coordinate implementation across matrixed data engineers, application teams, platform engineers, QE, and operations.
• Ensure pipelines meet non-functional requirements for performance, scalability, resiliency, availability, and cost efficiency.

• Architect and govern data validation, reconciliation, and control frameworks for all migrations.
• Ensure data completeness, accuracy, consistency, and referential integrity across source and target systems.
• Implement data lineage, auditability, and traceability to support regulatory, financial, and operational needs.
• Partner with Security, Privacy, and Compliance teams to enforce data protection, encryption, masking, and access controls.

• Manage technically complex, multi-stream data programs spanning multiple source systems and consumer platforms.
• Build and maintain detailed technical migration roadmaps, dependency maps, and milestone plans.
• Identify and mitigate risks related to data integrity, performance bottlenecks, schema drift, and operational readiness.
• Lead cutover execution, rollback planning, and post-migration stabilization.

• Define and enforce test strategies for data migrations, including unit testing, data reconciliation testing, performance testing, and business validation.
• Partner with QE and UAT teams to ensure business data correctness and outcome validation.
• Own technical production readiness reviews and go-live criteria.
• Ensure operational monitoring, alerting, and incident response mechanisms are implemented prior to go-live.

• Partner with Cloud and Platform teams to optimize infrastructure performance, reliability, and cost.
• Enable consumption-ready data models for analytics, reporting, APIs, and AI/ML workloads.
• Drive adoption of automation, Infrastructure-as-Code, and CI/CD for data pipelines.

• Serve as the primary technical authority for data migration and data platform delivery.
• Communicate complex technical risks, tradeoffs, and architecture decisions in business-relevant terms.
• Coordinate closely with Business, Product, Architecture, Analytics, PMO, and Operations leaders.

• Lead and mentor data engineering engineers, and technical leads.
• Establish engineering standards, design review practices, and technical governance.
• Build a culture of engineering rigor, automation, quality, and continuous improvement.

• Bachelor's degree in relevant field of study and 10+ years of relevant professional experience required.

• Additional years of relevant experience will be considered in lieu of degree. Master's degree preferred.
• 10+ years of experience in data engineering, data architecture, or large-scale platform modernization.
• 5+ years leading technically complex enterprise data migration programs.
• Deep experience migrating data from legacy systems (mainframe, on-prem relational/No
  
  SQL databases, proprietary platforms).
• Proven success delivering data platforms in cloud environments at enterprise scale.
• Experience leading delivery across matrixed engineering,…