Data ArchitectModeller Senior
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Monthly Salary:
Posted on:
16 hours ago
Vacancies:
1 Vacancy
Job Summary
Job Summary:
The Data Architect/Modeller role is responsible for leading the discovery assessment mapping and readiness of legacy data required for a provincial identity and access management (IAM) modernization program. This involves working with various teams to ensure data accuracy completeness and alignment with governance privacy and security expectations. The Data Architect will play a central role in defining how legacy data is understood transformed and migrated to support secure and scalable IAM operations.
The Data Architect/Modeller role is responsible for leading the discovery assessment mapping and readiness of legacy data required for a provincial identity and access management (IAM) modernization program. This involves working with various teams to ensure data accuracy completeness and alignment with governance privacy and security expectations. The Data Architect will play a central role in defining how legacy data is understood transformed and migrated to support secure and scalable IAM operations.
Location:Toronto Ontario Canada
Responsibilities:
- Lead structured discovery and documentation of legacy data.
- Develop current state data inventories dictionaries and conceptual data diagrams.
- Conduct data profiling and quality assessments to identify gaps risks and remediation needs.
- Define data quality rules acceptance thresholds and readiness criteria.
- Develop detailed source to target mappings aligned with the new solutions data model.
- Identify required transformations standardizations and enrichments.
- Support development of migration strategy sequencing and validation approaches.
- Collaborate with integration teams to clarify payloads field definitions and validation rules.
- Participate in testing and validation of migrated data.
- Produce high quality documentation for technical and business stakeholders.
- Align work with data governance privacy and security requirements.
- Present findings risks and recommendations to program leadership.
- Deliver a legacy data assessment with an inventory of legacy data sources structures and dependencies relevant to migration.
- Evaluate completeness accuracy duplication and integrity issues in source data.
- Define detailed source-to-target mappings between legacy systems and the logical future -state data model.
- Document cleansing normalization and transformation logic required during migration.
- Support verification of migrated data against source records to confirm accuracy and completeness.
- Provide data expertise and data sets to support integration system and UAT testing.
- Contribute to detailed functional requirements and acceptance criteria where data structures attributes or data flows must be defined.
- Support development of logical data model for target solution and mapping of it to SaaS data model identifying gaps to be addressed.
- Support data migration planning and transition activities.
- Lead structured discovery and documentation of legacy data.
- Develop current state data inventories dictionaries and conceptual data diagrams.
- Conduct data profiling and quality assessments to identify gaps risks and remediation needs.
- Define data quality rules acceptance thresholds and readiness criteria.
- Develop detailed source to target mappings aligned with the new solutions data model.
- Identify required transformations standardizations and enrichments.
- Support development of migration strategy sequencing and validation approaches.
- Collaborate with integration teams to clarify payloads field definitions and validation rules.
- Participate in testing and validation of migrated data.
- Produce high quality documentation for technical and business stakeholders.
- Align work with data governance privacy and security requirements.
- Present findings risks and recommendations to program leadership.
- Deliver a legacy data assessment with an inventory of legacy data sources structures and dependencies relevant to migration.
- Evaluate completeness accuracy duplication and integrity issues in source data.
- Define detailed source-to-target mappings between legacy systems and the logical future -state data model.
- Document cleansing normalization and transformation logic required during migration.
- Support verification of migrated data against source records to confirm accuracy and completeness.
- Provide data expertise and data sets to support integration system and UAT testing.
- Contribute to detailed functional requirements and acceptance criteria where data structures attributes or data flows must be defined.
- Support development of logical data model for target solution and mapping of it to SaaS data model identifying gaps to be addressed.
- Support data migration planning and transition activities.
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Preferred Skills & Certifications:
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