Data Analyst - Key Improvement (KI)

Our public sector client is looking for a Data Analyst to assess and implement changes across the enterprise data ecosystem. RFC-2026-039 Initially 6-month contract with chances of extension. Hybrid 2 days/week onsite in New West. 37.5 hours/week. Description The Enterprise Asset Management (EAM) Program is a strategic business transformation initiative focused on modernizing asset, maintenance, inventory, workforce, finance, and reporting capabilities through the implementation of enterprise technologies, data platforms, and analytics solutions. The program includes significant changes to operational systems, enterprise data structures, and business processes that require ongoing data analysis, enterprise data modelling, data engineering, reporting modernization, and Enterprise Data Warehouse (EDW) remediation activities. You will support the EAM Program by assessing and implementing changes across the enterprise data ecosystem, including redesigning and remodeling conceptual, logical, physical, dimensional, and semantic data models; evaluating impacts to EDW structures, integrations, reports, dashboards, and analytics solutions; supporting data quality and governance initiatives; and enabling trusted, scalable, and sustainable reporting and self-service analytics capabilities that support CMBC's operational and strategic objectives. Responsibilities Reporting to the CMBC EAM Reports Lead, you will provide the following services: Performs data analysis of Enterprise data and provides expertise and advice to business and tech stakeholders on the application of Data Management practices and principles. Performs detailed analyses of business areas to identify, understand, model and define data, business data flows and processes in conjunction with business and BTS stakeholders. Identifies data anomalies, patterns, overlaps and duplications and recommends improvements according to data management best practices and TransLink standards. Performs Enterprise Data Modelling and Data Architecture Services by: Analyzing business initiatives, system changes, and Enterprise Data Warehouse (EDW) impacts to assess effects on existing data structures, reporting models, and downstream consumers Performing data model impact assessments resulting from source system changes, business process changes, application implementations, and enterprise transformation initiatives Redesigning and remediating existing data models where required to support evolving business requirements, new data domains, and enterprise reporting capabilities Defining facts, dimensions, hierarchies, business rules, relationships, and conformed dimensions to support enterprise reporting and analytics solutions Developing dimensional, relational, and analytical data models for data warehouse, Lakehouse, semantic model, and reporting environments Working with business stakeholders, architects, report developers, and data engineers to translate business requirements into scalable enterprise data structures Assessing impacts to downstream reports, dashboards, semantic models, cubes, integrations, and data products resulting from data model modifications Identifying opportunities to simplify, standardize, consolidate, and optimize enterprise data structures while reducing duplication and improving maintainability Supporting enterprise reporting modernization efforts through the redesign and optimization of reporting and analytical data models Maintaining traceability between source systems, data transformations, business rules, data models, and reporting outputs Supporting data governance initiatives by ensuring data models align with enterprise standards, naming conventions, metadata requirements, and business definitions Participating in the review and approval of enterprise data architecture changes and providing recommendations related to data modelling best practices Develops and implements data quality control and monitoring solutions to support data quality for the enterprise by: Working with stakeholders to identify the impact of poor quality data on business areas Analyzing business, system and data requirements to identify data quality rules that need to be implemented to ensure data meets its business objectives Develop data quality procedures and processes to monitor and measure ongoing data quality levels Works with application support teams, the Data & Analytics team and system development project teams to offer Data Management expertise and services by: Defining and modeling data and data flows; Translating business requirements into data requirements; Creating data-related SDLC documentation deliverables according to standards including data requirements, data profiling, data quality assessments, technical and business metadata; Identifying and documenting data definitions for application business areas, ensuring that data is properly defined with minimal duplication and overlap; Ensuring that data definitions are consistent across the enterprise and identify where definitions and formats differ from standards; Assisting in the development of project plans and recommending the appropriate technical resources and cost estimations. Creates, designs and maintains the conceptual, logical and physical data models that form the Enterprise data architecture and updates the corporate metadata repository, ensuring the integrity and consistent definition and use of Enterprise data by: Creating conceptual, logical and physical data models; Gathering and documenting technical metadata and updating the technical metadata repository; Gathering and documenting business definitions and updating the business metadata repository; Defining and documenting business entities, attributes, hierarchies, relationships, and transformation roles; Documenting and maintaining source-to-target mappings between operational systems, integration layers, data warehouse, Lakehouses, and reporting layers. Keeps up to date with new developments in data management practices and technologies to support and improve data management services by: Reviewing and evaluating new data management tools and technologies; Executing service improvements to ensure data management services support Business Information and business needs; Makes recommendations and implements the enterprise data strategy. Performs data QA assurance tasks by: Reviewing and validating source-to-target data mappings Verifying data transformation logic Supporting test case development for data validation Executing data validation tests (pre- and post-load) Identifying and documenting data issues or discrepancies Collaborating with QA, developers, and business users during testing phases Supporting user acceptance testing (UAT) related to data accuracy Participating in defect triage and root cause analysis Requirements Hands-on experience with a range of Azure Services, including ADF, Azure Databricks, Delta Lake, Azure Data Lake Storage, Azure Synapse, Spark, Power BI Report, Microsoft Fabric. Strong knowledge and experience designing Data Warehouses. Strong knowledge of SQL Experience with Microsoft Azure Synapse is highly desirable. Logical and physical data modeling Experience supporting data governance and stewardship Exposure to enterprise data architecture Working with metadata repositories (technical and business) Understanding of enterprise-level data standards and definitions Experience working in Scrum Agile. For more current job opportunities, Follow MatchBox at linkedin.com/company/matchbox-recruitment/ _________________________ About MatchBox Headquartered in downtown Vancouver and serving clients nationally, MatchBox is one of the leading recruitment and solutions firms that specializes in the fields of IT & Technology, Engineering & Technical, Real Estate & Construction, and Accounting & Finance. We offer unrivaled expertise with our team's extensive experience in the recruitment and professional services industry. We are dedicated to building great connections and creating strong opportunities within the workforce and the labor market. Equal Opportunities MatchBox is committed to providing equal opportunities for all applicants. We welcome and encourage applications from people of all backgrounds, including members of minority groups such as racialized individuals, people with disabilities, LGBTQ+ individuals, and Indigenous peoples. It is a priority for us that all candidates are treated fairly and without discrimination. Our recruitment teams receive ongoing training on using objective criteria for evaluating candidates and other related topics to create an inclusive and welcoming environment for all. Work Permits Please note that we require all interested candidates to obtain the necessary work permits from the Government of Canada prior to submitting an application. This position is open exclusively to individuals residing in Canada and legally authorized to work in Canada. Applications not meeting these criteria will not be considered. Further Consideration We receive a high volume of applications and are only able to contact candidates who are selected for further consideration. Find out more at www.matchboxhr.com

The role involves assessing and implementing changes across the enterprise data ecosystem, including redesigning data models and remediating the Enterprise Data Warehouse. You will support data governance, quality monitoring, and the modernization of reporting and analytics capabilities.

Candidates need hands-on experience with Azure services (ADF, Databricks, Synapse) and strong SQL and data modeling skills. Experience with data governance, enterprise architecture, and working in a Scrum Agile environment is required.

• Power BISouhaitée
• SQLSouhaitée

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• Azure Data Factory
• Azure Databricks
• Delta Lake
• Azure Synapse
• Power BI
• SQL
• Data Modeling
• Data Governance
• Enterprise Data Architecture
• Scrum Agile
• Data Warehousing
• Microsoft Fabric
• Spark
• Data Quality Control
• Metadata Management
• ETL

• Data & Analytics
• Technology
• Government & Public Sector
• Transportation
• Consulting

Expérience minimale

5+ ans

Postuler avant le

17 sept. 2026

Langue de l’offre

anglais

Heures de travail

38 heures par semaine

Présence au bureau

2 jours par semaine

Niveau d’expérience

Entry level

Mode de candidature

La candidature directe est offerte