Senior Data Engineer - Toronto
Confirmed on the employer's own hiring board on Oct 15, 2026. First seen by Alion on Sep 24, 2026.
We are currently seeking a driven and collaborative Senior Data Engineer to join our forward-thinking Data and Analytics team.
SENIOR DATA ENGINEER
TORONTO
Position Overview:
As a Senior Data Engineer on our Data & Analytics Team, you will be a hands-on technical leader responsible for designing, building, operating, and continuously improving scalable, secure, and reliable data solutions. The role will help modernize Trisura’ s data platform, enable trusted analytics and reporting, and establish engineering standards across ingestion, transformation, orchestration, deployment, monitoring, data quality, and documentation.
Working closely with Data & Analytics, application teams, architects, analysts, governance, and business stakeholders, the Senior Data Engineer will translate business requirements into reusable data products and production-grade solutions across Microsoft Fabric, Azure, SQL Server, Power BI, and related technologies.
What you will do:
Design, build, test, deploy, and support scalable batch and near-real-time data pipelines for structured, semi-structured, and unstructured data using Microsoft Fabric, Azure Data Factory, SSIS, SQL Server, Azure SQL, cloud storage, and other enterprise data sources.
Develop modern data engineering solutions using Microsoft Fabric capabilities such as Lakehouse, Warehouse, OneLake, Copy Jobs, Notebooks, Dataflow Gen2, and related services, applying layered bronze/silver/gold architecture patterns where appropriate.
Develop robust, reusable ETL/ELT and data transformation solutions using T-SQL, Python, PySpark, and Spark SQL, including incremental loading, Change Data Capture (CDC), schema evolution, reconciliation, restart/recovery, idempotency, and error-handling patterns.
Design dimensional, relational, and Lakehouse data models that support analytics, operational and regulatory reporting, self-service analytics, and downstream system integrations.
Ensure production reliability by implementing monitoring, alerting, logging, data quality controls, reconciliation, metadata, lineage, auditability, and operational support procedures.
Optimize SQL, Spark, pipeline, and storage workloads for performance, scalability, reliability, and cost efficiency while applying security and privacy best practices, including least-privilege access, managed identities, service principals, secrets management, secure connectivity, and environment separation.
Implement source control, automated deployment, and CI/CD practices using Git, Azure DevOps, and Microsoft Fabric deployment capabilities, and participate in code reviews, testing, release planning, incident resolution, root-cause analysis, and post-implementation reviews.
Develop reusable engineering standards, frameworks, templates, patterns, and technical documentation to improve consistency, maintainability, and operational support across the data platform.
Partner with Power BI developers, analysts, business stakeholders, Data Governance, and other technology teams to translate business requirements into trusted, well-structured data solutions and clearly communicate dependencies, risks, and technical trade-offs.
Support the modernization and migration of legacy SSIS, SSRS, Azure Data Factory, SQL-based, and other data integration workloads to strategic cloud and Microsoft Fabric platforms.
What You Bring:
Core Skills:
Strong ownership, accountability, and a focus on delivering reliable, maintainable data solutions.
Ability to lead technical design discussions, mentor other engineers, and promote engineering best practices.
Excellent written and verbal communication skills, including the ability to explain complex technical concepts to technical and non-technical audiences.
Ability to thrive in a fast-paced environment, manage competing priorities, and independently drive work from requirements through production support.
A collaborative and customer-focused mindset when working with business stakeholders, analysts, developers, architects, vendors, and operational teams.
Strong analytical and troubleshooting skills with a focus on root-cause analysis, automation, and continuous improvement.
Technical Expertise:
Advanced SQL and T-SQL skills, including complex querying, stored procedures, views, indexing, execution-plan analysis, performance tuning, and query optimization.
Strong Python skills for data engineering, automation, testing, API integration, and file processing, with hands-on experience in PySpark and Spark SQL preferred.
Hands-on experience with Microsoft Fabric and Azure data services, including Lakehouse, Warehouse, OneLake, Delta tables, pipelines, notebooks, Azure Data Factory, Azure SQL Database/Managed Instance, Azure Data Lake Storage, and Key Vault.
Strong understanding of modern data architecture and engineering patterns, including data warehousing, Lakehouse architecture, dimensional modeling, medallion architecture, ETL/ELT, incremental processing, and enterprise data integration.
Experience with Git-based source control, branching and pull-request practices, automated testing, CI/CD, and environment-specific configuration and deployment.
Experience designing secure data solutions using Microsoft Entra ID, managed identities, service principals, role-based access control, secrets management, and least-privilege principles.
Knowledge of data observability and governance practices, including logging, monitoring, alerting, pipeline metrics, reconciliation, metadata, lineage, data quality, retention, reference/master data, and audit requirements.
Working knowledge of Power BI and semantic model consumption patterns; experience with DAX is considered an asset.
Experience integrating enterprise databases, REST APIs, JSON, CSV, Parquet, Delta, SFTP, and other file-based or application data sources.
Experience with PostgreSQL and legacy Microsoft technologies such as SSIS and SSRS is an asset, particularly in modernization and migration initiatives.
Ability to develop clean, modular, testable, maintainable, and well-documented production-quality code.
Qualifications
Bachelor's degree, college diploma, or equivalent practical experience in Computer Science, Information Systems, Data Engineering, Software Engineering, or a related field.
Minimum 5 years of progressive experience in data engineering, data integration, data warehousing, analytics engineering, or related roles, including ownership of production data solutions.
Demonstrated experience designing and delivering end-to-end data solutions rather than only developing individual ETL components or reports.
Demonstrated experience troubleshooting complex production data issues and improving platform reliability, performance, and maintainability.
Experience providing technical leadership, mentoring, code review, solution design, or engineering standards is strongly preferred.
Experience in Insurance or another regulated financial-services environment is strongly preferred.
Microsoft Fabric, Azure Data Engineer, Azure, Power BI, or related Microsoft certifications are considered an asset.
Location:
Downtown Toronto – Hybrid
Salary:
The maximum potential base salary for this position is $125,000
This salary range reflects the expected base compensation for the role across Canada. Actual compensation will be determined based on factors such as experience, qualifications, and scope of responsibilities. Trisura provides this range in good faith in accordance with applicable legislation.
This position is for an existing, currently vacant position.
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