Data Architect

Identify, catalogue, and document relevant data sources, including system endpoints, APIs, database schemas, and file formats for prioritized business workflows.

Assess data availability, accuracy, completeness, consistency, and timeliness to evaluate data readiness for prioritized workflows.

Perform data quality assessments to identify anomalies, duplicate records, missing values, and inconsistencies. Document data quality metrics, scores, and recommendations for remediation.

Define data transformation and mapping strategies to convert raw data into Advanced Distribution Management System (ADMS)-ready formats, including field mapping, unit conversions, data standardization, and data model alignment.

Develop and maintain comprehensive data architecture documentation covering database structures, ETL processes, data integration workflows, and data storage strategies.

Establish authoritative data sources and maintain end-to-end data lineage across current-state and future-state platforms to ensure data traceability, consistency, and governance.

Support the identification and assignment of data governance roles, including Data Owners, Data Stewards, and Data Custodians, across business and technical teams.

Conduct data gap analysis to identify missing data elements, integration gaps, quality issues, and discrepancies between existing data assets and target-state architecture requirements.

Develop and enhance conceptual data models by mapping current-state data structures to the target-state architecture, identifying data relationships, dependencies, and transformation requirements.

Assess data transiency, lifecycle requirements, and data exchange patterns for edge applications, ensuring alignment with integration standards and target-state architecture.

Collaborate with business stakeholders, application teams, and technical architects to validate data requirements, resolve data gaps, and support seamless integration with ADMS and related utility applications.

Ensure data architecture deliverables align with enterprise data standards, data governance policies, integration requirements, and overall solution architecture objectives.