Data Analyst (6+ years of experience) to support enterprise data modelling, ETL/ELT development, and analytics modernization using Microsoft Fabric and Azure Synapse RFC-2026-039
S.I. Systems Ltd.
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Benefits offered by this job
Job summary
S.I. Systems Ltd. is seeking a Data Analyst with 6+ years of experience to support enterprise data modelling, ETL/ELT development, and analytics modernization using Microsoft Fabric and Azure Synapse.
The role focuses on data flows, governance, and scalable data solutions within a Vancouver hybrid setting. Responsibilities include designing pipelines, maintaining models, and ensuring data quality across analytics and reporting environments.
Qualifications
- Hands-on with Microsoft Fabric, Azure Synapse, Azure Data Factory and Azure Data Lake Storage.
- Strong SQL and Data Warehousing design knowledge.
- Experience with Python, PySpark, ETL/ELT development and data integration.
- Experience with logical and physical data modeling, data architecture and metadata repositories.
- Experience supporting Data Governance, data quality frameworks and Scrum/Agile.
Responsibilities
- Perform enterprise data analysis and define data flows, business rules and data requirements.
- Design and maintain data ingestion, transformation and orchestration pipelines using Microsoft Fabric and Azure technologies.
- Develop ETL/ELT processes to support reporting, analytics and operational data solutions.
- Create and maintain conceptual, logical, physical, dimensional and semantic data models.
- Assess impacts to Enterprise Data Warehouse structures, integrations, reports and dashboards.
- Develop data quality monitoring procedures, validation processes and data QA activities.
- Document metadata repositories, source-to-target mappings, data definitions and SDLC deliverables.
Skills
Tools
Job description
Our transportation client is seeking a Data Analyst (6+ years of experience) to support enterprise data modelling, ETL/ELT development, and analytics modernization using Microsoft Fabric and Azure Synapse
Join a large-scale Enterprise Asset Management transformation initiative focused on modernizing enterprise reporting, analytics, and operational data capabilities. This role supports enterprise data analysis, data engineering, data modelling, and data quality initiatives across operational systems, reporting environments, and Enterprise Data Warehouse remediation activities. The position works closely with business stakeholders, data engineers, architects, and reporting teams to support scalable and sustainable enterprise data solutions.
6 month Contract, high chance of extension, Vancouver, Hybrid 2 days a week, Working Hours: 37.5 hours PST
- Hands-on experience with Microsoft Fabric, Azure Synapse, Azure Data Factory, and Azure Data Lake Storage
- Strong knowledge of SQL and Data Warehousing design
- Experience with Python, PySpark, ETL/ELT development, and enterprise data integration
- Experience with Logical and Physical Data Modeling, enterprise data architecture, and metadata repositories
- Experience supporting Data Governance, data quality frameworks, and Scrum Agile
- Experience with Microsoft databases
- Experience with Azure Databricks and Delta Lake
- Experience preparing test cases and scripts for data testing
- Exposure to Power BI Report development
Responsibilities
- Perform enterprise data analysis and define data flows, business rules, and data requirements
- Design and maintain data ingestion, transformation, and orchestration pipelines using Microsoft Fabric and Azure technologies
- Develop ETL/ELT processes supporting enterprise reporting, analytics, and operational data solutions
- Create and maintain conceptual, logical, physical, dimensional, and semantic data models
- Assess impacts to Enterprise Data Warehouse structures, integrations, reports, dashboards, and downstream data consumers
- Develop data quality monitoring procedures, validation processes, and data QA activities
- Document metadata repositories, source-to-target mappings, data definitions, and SDLC data deliverables
Our transportation client is seeking a Data Analyst (6+ years of experience) to support enterprise data modelling, ETL/ELT development, and analytics modernization using Microsoft Fabric and Azure Synapse
Join a large-scale Enterprise Asset Management transformation initiative focused on modernizing enterprise reporting, analytics, and operational data capabilities. This role supports enterprise data analysis, data engineering, data modelling, and data quality initiatives across operational systems, reporting environments, and Enterprise Data Warehouse remediation activities. The position works closely with business stakeholders, data engineers, architects, and reporting teams to support scalable and sustainable enterprise data solutions.
6 month Contract, high chance of extension, Vancouver, Hybrid 2 days a week, Working Hours: 37.5 hours PST
Must Haves- Hands-on experience with Microsoft Fabric, Azure Synapse, Azure Data Factory, and Azure Data Lake Storage
- Strong knowledge of SQL and Data Warehousing design
- Experience with Python, PySpark, ETL/ELT development, and enterprise data integration
- Experience with Logical and Physical Data Modeling, enterprise data architecture, and metadata repositories
- Experience supporting Data Governance, data quality frameworks, and Scrum Agile
Nice to Have- Experience with Microsoft databases
- Experience with Azure Databricks and Delta Lake
- Experience preparing test cases and scripts for data testing
- Exposure to Power BI Report development
Responsibilities- Perform enterprise data analysis and define data flows, business rules, and data requirements
- Design and maintain data ingestion, transformation, and orchestration pipelines using Microsoft Fabric and Azure technologies
- Develop ETL/ELT processes supporting enterprise reporting, analytics, and operational data solutions
- Create and maintain conceptual, logical, physical, dimensional, and semantic data models
- Assess impacts to Enterprise Data Warehouse structures, integrations, reports, dashboards, and downstream data consumers
- Develop data quality monitoring procedures, validation processes, and data QA activities
- Document metadata repositories, source-to-target mappings, data definitions, and SDLC data deliverables
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