Sr. Data Engineer to support the implementation of an end-to-end analytics solution using Microsoft Fabric to ingest data from various sources, create a se

Our valued client is looking for a Sr. Data Engineer to support the implementation of an end-to-end analytics solution using Microsoft Fabric to ingest data from various sources, create a semantic models, and enable dashboard/visualization creation for the business team.

Annual Salary approximately from $94,580.00 - $111,320.00 per year

This is a hybrid position (2 days/week on site) in Ottawa

Tasks include:

• Implementing an end-to-end analytics solution using Microsoft Fabric to ingest data from various sources, create a semantic models, and enable dashboard/visualization creation for the business team
• Assist the data management team in implementing data governance frameworks, policies, and controls including classification, sensitivity, access controls, and quality validation
• Design and implement data pipelines in Microsoft Fabric, including source mapping and documentation, create and optimize semantic models including defining business entities, relationships, and security requirements
• Set up development, testing, and production environments
• Create comprehensive technical documentation covering configurations, data models and business rules

Prior experience:

• Must be eligible for or possess a reliability clearance
• Data modeling methodologies (Star schema, Snowflake schema; Data Vault is an asset)
• End-to-end data pipeline development, optimization, and monitoring
• Data quality frameworks, validation techniques, and data profiling
• Database platforms (SQL Server, Azure SQL; Oracle is an asset)
• Fabric/Power BI semantic model development and DAX optimization
• Multi-platform data integration and ETL/ELT design patterns
• Lakehouse and Medallion Architecture implementation
• Data lineage documentation and data mapping
• Technical documentation and solution design
• Applying organizational policies, procedures, and data governance regulations

Technical Skills

• Microsoft Fabric (Data Factory, data pipelines, lakehouses, warehouses, notebooks, Spark job definitions)
• Power BI (semantic modeling, DAX, Power Query M, dataflows)
• SQL (advanced T-SQL, stored procedures, query optimization)
• Spark (PySpark, Spark SQL, Delta Lake)
• Python for data engineering and transformation
• ETL/ELT design patterns and best practices
• Lakehouse and Medallion Architecture (Bronze/Silver/Gold)
• Azure data services (Azure Data Lake Storage Gen2, Azure Synapse Analytics, Azure SQL)
• Version control (Git) and Azure DevOps CI/CD
• SSIS, SSRS, SSMS (an asset)