Senior Data Architect

Senior Data Architect who will provide technical leadership to our project teams to successfully deliver mid to large size initiatives in the Greater Toronto Area.
Salary: 100K+
RESPONSIBILITIES
Provide the overall information and data strategy and solution for client engagements based on an approach that is holistic, scalable, pragmatic, and effective structuring of data and information.
Understand business needs for data and information especially in the Banking and Financial Industries.
Develop data architecture (data definitions, data flows, identification of data sources and data consumers, business rules and transformations, and data models) for client engagements.
Design data models (conceptual or logical) that are adaptable, extensible, and sustainable.
Define data management and data improvement processes as part of the overall enterprise data strategy.
Perform data profiling and data quality audit.
Produce estimates for data requirement analysis, data model design, and ETL design. ​
Review and guide the technical team’s deliverables to ensure overall data quality and information structure compliance with the overall data architecture.
Ensure compliance with business, data, and technical requirements.
Ensure that enterprise architecture standards, policies, and procedures are enforced.​
Provide assessments of architectural risk and mitigation strategies.​
Mentor and coach the technical team.
Assist with proposals and pre-sales.
REQUIREMENTS
Minimum 15 years experience in Information Technology, participating in complex projects.
Minimum Bachelors degree in Computer Science.
Strong Communication skills.
Strong business and IT knowledge and experience in the Banking and Financial Industries.
Proven Leadership skills.
Strong skill in Information Needs Analysis and Data Quality Audit.
Strong Data Warehousing Architecture knowledge (e.g. enterprise data warehouse, master data management, data integration, and data quality).
Strong knowledge in Data Warehousing Life Cycle and Data Integration Methodologies (ETL, EAI, EII).
Strong knowledge and experiences in both Relational and Dimensional Data Modeling  – with both Kimball and Inmon approaches.
Integration experiences with industry or vendor data models.
Working knowledge of ERwin and other data modeling tools.
Working SQL knowledge in Oracle BIEE or Microsoft SQL, SSRS, SSIS and or Informatica.
Knowledge in data management principles.
Ability to work concurrently on multiple initiatives and excel in a team environment.

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