Data Architect - Information Systems

- Oversee the delivery of data architecture at both project and domain levels - Collaborate with business stakeholders, solution architects, and engineering teams - Collect, analyze, and validate business and technical data needs; convert requirements into conceptual, logical, and physical data models - Design and maintain enterprise data models, database schemas, and messaging frameworks for transactional systems, ODS, data warehouses, and analytics - Ensure that data designs align with the enterprise reference architecture, data standards, naming conventions, and compliance regulations - Establish and uphold data integration architectures, patterns, and roadmaps that are consistent with the enterprise data strategy - Provide technical guidance for ETL and data integration development across various platforms including Azure Data Factory and Synapse - Draft and manage source-to-target mappings, transformation logic, business rules, and data integration documents - Collaborate with business and product stakeholders to define KPIs, metric definitions, and shared metric catalogs for uniformity in analytics and reporting - Develop and maintain curated analytics datasets and semantic models to enhance dashboards and self-service reporting capabilities - Conduct data profiling, reconciliation, and validation with SQL and Python to ensure data integrity, completeness, and consistency - Specify data validation rules and testing scenarios; support QA, UAT, and production readiness efforts - Participate in data governance processes including metadata management, documentation of lineage, certified datasets, and reduction of redundant data assets - Create and sustain processes for capturing and managing metadata across operational, integration, and analytical platforms - Collaborate with application, infrastructure, and integration teams to guarantee comprehensive information flow across systems - Lead or engage in architecture design sessions and reviews, identifying risks and suggesting mitigation methods - Provide coaching and mentorship to data engineers, analysts, and junior architects while promoting best practices in modeling and integration - Assist in project planning, estimations, and delivery tasks; contribute to technical designs and implementation strategies - Research and implement cutting-edge data architecture patterns, cloud best practices, and emerging technologies to enhance performance and scalability