Senior Data Engineer
Ontario Municipal Employees Retirement System1 month ago
Toronto, CanadaSenior
Responsibilities
- Translate business requirements into scalable, secure, and reliable data solutions.
- Design, develop, deploy, and operate cloud data platforms, pipelines, and data products.
- Source, transform, and deliver structured and unstructured data for analytics, reporting, operational, and AI-enabled use cases.
- Develop and maintain reliable, scalable, performant, and secure ELT/ETL pipelines.
- Define and execute unit, integration, performance, data quality, and automated regression testing strategies.
- Optimize data pipelines, data models, and platform components for performance, cost efficiency, and operational excellence.
- Implement CI/CD, monitoring, observability, auditing, and operational controls for production-grade solutions.
- Provision and manage Azure resources with appropriate security, governance, and cost management.
- Troubleshoot complex technical issues, trace data lineage, and drive continuous improvement across data solutions and platforms.
- Provide technical leadership and integration expertise while collaborating with business and technology stakeholders.
Requirements
- At least 5 years of experience delivering complex data engineering and analytics solutions using Microsoft Azure.
- Enterprise-scale experience designing, building, and supporting cloud-based data platforms, data products, and scalable ELT/ETL solutions on Azure.
- Strong hands-on experience with Python, PySpark, and SQL.
- Deep expertise in Snowflake and dbt, including data modeling, transformation, testing, deployment, and performance optimization.
- Strong experience with data architecture, data modeling, data warehousing, and dimensional modeling methodologies such as Kimball and Data Vault 2.0.
- Experience with data orchestration tools such as Prefect, Dagster, Airflow, Azure Data Factory, or Synapse.
- Experience designing and developing Azure Functions and Azure Logic Apps for data integration, automation, and event-driven solutions.
- Experience implementing and maintaining CI/CD pipelines using GitHub Actions.
- Strong analytical, troubleshooting, stakeholder collaboration, documentation, and technical relationship-building skills.
- Experience designing data solutions for AI-enabled use cases, semantic search, or unstructured data processing.
- Preferred experience in financial services, asset management, pension, investment management, or similar data-intensive industries.
- Preferred experience with Azure Databricks, Microsoft Fabric, Power BI, containerization, container orchestration, Infrastructure-as-Code, and cloud automation.
- Preferred post-secondary education in Computer Science, Software Engineering, Information Technology, or a related discipline.
Benefits
- Flexible hybrid work arrangement requiring teams to work in the office four days per week.
- Eligibility for annual incentive awards under short-term and, where applicable, long-term incentive plans.
- Group benefits and retirement plans.
- Inclusive, barrier-free workplace with employee resource groups, employee recognition programs, and a Purpose@Work committee.
Categories
Data Engineering