Data Engineer; Azure​/Databricks

About the Company

Our client is a leading Canadian energy organization with a strong presence across Ontario. They operate critical infrastructure that supports millions of customers and drives economic growth.

Our client is engaging in ongoing transformation and investing in cutting-edge technologies and modernizing operations to meet the evolving needs of the energy sector. By joining, you will be part of an organization that values collaboration, professional development, and making a meaningful impact on the future of clean energy.

• Architect, design, and oversee implementation of modular and scalable ELT/ETL pipelines and infrastructure.
• Design curated, business centric data models that provide a single source of truth for reporting and analytics.
• Collaborate with infrastructure and security teams to ensure data protection in transit and at rest.
• Establish and enforce code templates for pipeline delivery across structured, semi-structured, and unstructured datasets.
• Develop modeling guidelines for facts, dimensions, aggregates, and slowly changing dimensions.
• Optimize join performance and extensibility across multi-domain physical and semantic models.
• Transform data into semantic layers that align with business language and usability.
• Partner with analysts, scientists, engineers, and architects to deliver pipelines feeding enterprise data marketplaces.
• Introduce new technologies through research and proof-of-concepts, preparing production-ready designs.
• Work with Microsoft Azure tools including Data Factory, Data Lake, SQL Databases, Synapse, Databricks, Purview, and Power BI.
• Contribute within agile SCRUM frameworks, supporting backlog development and iterative delivery.
• Document architecture and designs, ensuring clarity and traceability.
• Design solutions for batch, near-real-time, event-driven, and streaming data requirements.
• Ensure orchestration of pipeline execution meets latency expectations and dependency management.
• Approve production deployments and provide Tier 3 support for troubleshooting.
• Guide teams in building models optimized for KPIs, operational feedback, and machine learning predictability.

• Bachelor’s degree in computer science, Software Engineering, or a related field (advanced education in data engineering, AI, or ML is an asset).
• 6–8 years of experience in data modeling, data warehouse design, and solution architecture in Big Data environments.
• Proven expertise in designing data models to solve business problems and specifying pipeline design patterns.
• Experience guiding data lake ingestion and modeling projects in cloud environments (Azure and Databricks).
• Strong background in relational and in-memory modeling, including star and snowflake schemas.
• Experience designing event-driven, near-real-time, or streaming data solutions across structured and unstructured sources.
• Advanced knowledge of data pipeline optimization, low-latency processing, and creation of common data models.
• Strong analytical and problem-solving skills, with a focus on scalability, performance, and maintainability.
• Excellent communication and leadership skills, with the ability to mentor and influence cross-discipline teams.

$87.58 - $97.58/hr