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The Data Warehouse Expert will provide specialized consulting, technical oversight, and project management support during Phase 3 of the project. The role is responsible for overseeing the implementation, integration, and optimization of the Data Warehouse solution, ensuring alignment with approved architecture, data governance standards, performance requirements, and project timelines through to the issuance of the Final Acceptance Certificate (FAC).
The consultant will work closely with system integrators, data engineers, vendors, and stakeholders to ensure the Data Warehouse solution is delivered, validated, and fully operational.
Monitor and oversee Data Warehouse implementation activities to ensure adherence to the approved project plan, scope, timelines, and milestones.
Support the client in tracking progress, risks, issues, and dependencies related to data platforms and analytics deliverables.
Ensure compliance with contractual, architectural, and data governance requirements.
Provide expert guidance on Data Warehouse architecture, data models, ETL/ELT pipelines, and integration approaches.
Review and validate logical and physical data models, data integration designs, and implementation documents.
Ensure scalability, performance, security, and reliability of the Data Warehouse solution.
Oversee integration of data from multiple source systems, including transactional systems, applications, and third -party platforms.
Ensure data accuracy, consistency, completeness, and timeliness across the Data Warehouse.
Support the definition and enforcement of data quality, metadata management, and master data standards.
Facilitate coordination between system integrators, data engineers, BI/analytics teams, and business stakeholders.
Participate in project meetings, design reviews, technical workshops, and status reporting.
Act as a subject matter expert and trusted advisor to the client on Data Warehouse–related matters.
Support and oversee data validation, reconciliation, and testing activities.
Review results of system testing, integration testing, and user acceptance testing (UAT).
Ensure performance tuning, optimization, and issue resolution during implementation.
Identify, analyze, and resolve technical or operational challenges related to data ingestion, transformation, storage, and reporting.
Provide hands -on technical support in specialized data domains as required during the implementation phase.
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