Data Integration Engineer - Contract

Softchoice • Toronto, ON

4d

About The Position

As a senior member of the Data Engineer team, you will be responsible for leading the design, development, and optimization of enterprise-grade data solutions within the Microsoft Fabric ecosystem. This role requires deep technical expertise, strategic thinking, and the ability to mentor junior engineers while collaborating with cross-functional teams. You will work closely with data scientists, analysts, and other stakeholders to ensure seamless data integration, transformation, and storage, enabling data-driven decision-making across the organization. This role is a fixed 6-month contract term.

Requirements

• Proficient in SnowSQL, stored procedures, tasks, and data loading/unloading (COPY INTO).
• Experience with Microsoft Fabric: Data Factory pipelines, Dataflow Gen2, and OneLake integration.
• Expertise in Spark/Python (PySpark) for data transformation, or ELT tools.
• Advanced SQL knowledge is essential for complex transformations.
• 5+ years of experience working on complex data integration and pipeline development across a variety of systems.
• Proven ability to design and orchestrate complex data integrations, leveraging Data Factory, REST APIs, and other enterprise data sources.
• Leadership in defining and executing scalable ELT strategies using Spark notebooks, Data Factory, and Synapse pipelines.
• Advanced knowledge of data pipeline optimization, including performance tuning and workload configuration.
• Experience establishing naming conventions, workspace governance, and CI/CD deployment strategies.
• Leadership in data governance, including sensitivity classifications, security models, and access control frameworks.
• Ability to build and maintain monitoring, alerting, and automated testing for ADF pipelines and data assets.
• Ability to align Microsoft Fabric implementations with enterprise data strategy and long-term growth plans.
• Hands-on experience using AI coding agents and AI-assisted development tools in a data engineering context; comfort integrating AI into daily development workflows and evangelizing adoption across the team.
• Strong problem-solving skills and ability to work in a collaborative environment.
• Excellent verbal, written, communication, presentation, organizational, and interpersonal skills.

Nice To Haves

• Preferred Microsoft Fabric certification – DP600, DP700.

Responsibilities

• Design, develop, and maintain data pipelines to move data between Microsoft Fabric (Lakehouse/Warehouse) and Snowflake, often utilizing Fabric Data Factory.
• Set up connectors, mirroring, or Spark notebooks to sync data from OneLake to Snowflake, including handling incremental loads.
• Build and optimize data models (Star Schema/Data Vault) within Snowflake and Fabric for high-performance querying.
• Monitor and optimize Fabric to Snowflake compute usage and ensure efficient data movement.
• Ensure data security during transfer, using tools like Snowflake RBAC, Dynamic Data Masking, and Fabric's security features.
• Design and orchestrate complex integrations across Data Factory, REST APIs, and other enterprise data services.
• Lead scalable ELT strategies using Spark Notebooks, Data Factory, and Synapse Pipelines.
• Develop reusable, optimized Spark jobs and configure compute pools for cost-efficient performance.
• Establish naming conventions, workspace governance, and CI/CD deployment strategies across Fabric.
• Build monitoring dashboards, alerts, and automated testing for pipelines and operations.
• Leverage AI coding agents and AI-assisted development tools (e.g., GitHub Copilot, Windsurf, or similar) to accelerate data engineering workflows, automate repetitive tasks, and improve code quality across the Fabric ecosystem.

Benefits

• Flexibility: Plan your workdays in a way that suits you best
• Award-Winning Workplace: Proudly recognized as a Great Place to Work for 20 consecutive years
• Inclusive Culture: We are committed to an inclusive culture where every team member can be their authentic self

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed