Data Architect

The Data Architect will play a key leadership and architecture role across two major areas:  Application Data Migration  and the subsequent  design and implementation of the enterprise Data Platform .   The role will be responsible for analyzing complex application data migration requirements, defining the end-to-end migration architecture and approach, guiding execution and testing, and ensuring successful transition of data from legacy/source applications to target systems.   Following the migration program, the Data Architect will lead the architecture and implementation of the target Data Platform, including data ingestion and ETL/ELT pipelines, data storage and processing capabilities, reporting and analytics solutions, and enterprise data governance capabilities such as data cataloging, lineage, security, quality, and metadata management.   The role requires strong architecture expertise combined with hands-on understanding of data engineering, migration, analytics, and data governance, as well as the ability to work closely with business, application, infrastructure, security, and implementation teams.

Required Experience and Skills:  Significant experience in Data Architecture, Data Engineering, Data Migration, and enterprise Data Platform implementation.  Proven experience designing and delivering application data migration programs.  Strong understanding of relational databases, data models, data warehouses, data lakes, lakehouse architectures, and analytical platforms.  Strong knowledge of ETL/ELT architecture, data integration patterns, APIs, batch processing, Change Data Capture, and data orchestration.  Experience designing scalable cloud data platforms on MS Fabric.  Strong understanding of data migration methodologies, source-to-target mapping, transformation, reconciliation, and migration testing.  Experience with enterprise BI and analytical architectures, including semantic models, data marts, reporting, and dashboards.  Strong understanding of data governance concepts including data cataloging, metadata management, data lineage, data quality, data ownership, and stewardship.  Strong knowledge of data security, privacy, data classification, access control, encryption, masking, and regulatory considerations.

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