Senior Data Performance Engineer | Azure Synapse | Power BI | Spark | Data Platform Optimization

Senior Data Performance Engineer | Azure Synapse | Power BI | Spark | Data Platform Optimization

Montreal, QC (Hybrid - 3 days onsite)

Salary: Up to $100,000 CAD

Are you passionate about solving complex data performance challenges and optimizing enterprise-scale analytics platforms? We are seeking a Senior Data Performance Engineer who can take a holistic view of the data ecosystem, from source systems and ETL processes to Azure Synapse and Power BI reporting. This role is ideal for someone who enjoys investigating bottlenecks, improving scalability, and driving measurable performance gains across modern cloud-based data platforms.

You will work closely with data engineering, analytics, and business teams to identify root causes of performance issues, optimize data processing workloads, and enhance reporting efficiency. The successful candidate will be a hands-on expert in Azure Synapse, SQL optimization, Spark, and Power BI, with the ability to troubleshoot and improve end-to-end data flows in a large enterprise environment.

Key Responsibilities

• Optimize Azure Synapse Analytics environments and workloads.
• Improve performance of Synapse Pipelines and Azure Data Factory processes.
• Analyze and enhance Data Lake architectures.
• Design and optimize ETL/ELT processes for efficiency and scalability.
• Troubleshoot large-scale data processing and integration challenges.

SQL & Data Warehouse Optimization

• Perform advanced SQL query tuning and performance analysis.
• Analyze execution plans and identify optimization opportunities.
• Optimize Synapse SQL Pools.
• Implement best practices for partitioning, indexing, and statistics management.
• Enhance data warehouse architecture and performance.

Power BI Performance Engineering

• Optimize datasets and semantic models.
• Implement and maintain Incremental Refresh strategies.
• Improve performance of DirectQuery and Import models.
• Tune DAX calculations and measures.
• Analyze report refresh processes and Power BI capacity utilization.
• Develop and optimize solutions using PySpark and Spark SQL.
• Improve performance of distributed Spark workloads.
• Manage data partitioning strategies and file optimization techniques.
• Leverage Azure Monitor and Log Analytics for performance monitoring.
• Conduct end-to-end platform performance assessments.
• Compare UAT and Production environments to identify discrepancies.
• Lead structured troubleshooting and root cause analysis initiatives.

Required Qualifications

• Strong experience with Azure Synapse Analytics and enterprise data platforms.
• Expertise in SQL performance tuning and data warehouse optimization.
• Hands-on experience with Power BI performance troubleshooting.
• Strong knowledge of PySpark, Spark SQL, and large-scale data processing.
• Experience with Azure monitoring and diagnostic tools.
• Ability to analyze complex data workflows and recommend performance improvements across the entire data lifecycle.