Intermediate Data Engineer

Location: Toronto, ON

Work model: 4 days onsite

Type: Contract

Duration: 12 months

Rate: 80-90/HR INC

About the Opportunity

We are seeking a Data Engineer with experience in data engineering, cloud technologies, and machine learning operations to support the development and improvement of data capabilities.

In this role, you will build, maintain, and enhance data pipelines that support analytics, machine learning, and AI applications. You will work with data scientists, technology teams, and business stakeholders to connect data sources, improve data quality, and enable reliable delivery of data to analytical models and downstream systems.

The ideal candidate is a hands-on engineer who can work through complex technical challenges, understand business requirements, and translate them into practical, scalable solutions.

Key Responsibilities

• Design, develop, and maintain data pipelines that support analytics, machine learning, and AI applications.
• Build and optimize data integrations, transformations, and preprocessing workflows across multiple source systems.
• Develop and maintain solutions using Python, SQL, and cloud-based data engineering tools.
• Support the deployment, integration, monitoring, and ongoing improvement of machine learning models and associated pipelines.
• Contribute to the migration and modernization of data processes and platforms into cloud-based environments.
• Prepare and structure data for predictive models, advanced analytics, and AI applications, including large language model use cases.
• Troubleshoot pipeline issues, improve data reliability, and identify opportunities to enhance performance and efficiency.
• Collaborate with data scientists, developers, and business stakeholders to understand requirements and deliver effective technical solutions.
• Translate business needs into clear technical requirements and actionable development plans.
• Document processes, technical solutions, and data workflows to support maintainability and knowledge sharing.

Required Qualifications

• Approximately 4+ years of experience in data engineering, data integration, or a related technical role.
• Strong programming experience with Python.
• Hands-on experience with SQL and data transformation.
• Experience with cloud-based data platforms and services; AWS is preferred.
• Familiarity with PySpark or other distributed data processing technologies.
• Experience building and maintaining data pipelines for analytics, machine learning, or AI applications.
• Understanding of machine learning operations, including model deployment, integration, monitoring, or production support.
• Experience working with multiple data sources and transforming complex datasets into usable formats.
• Strong analytical and problem-solving skills, with the ability to break complex requirements into manageable steps.
• Excellent communication skills and the ability to collaborate across technical and business teams.

Nice to Have

• Experience with SAS or supporting the migration of legacy data processes to Python.
• Exposure to machine learning platforms, AI integrations, or large language model workflows.
• Experience in financial services or another complex, regulated environment.
• Familiarity with data governance, data quality, and production data management practices.

What Makes You a Great Fit

You are a practical, solutions-oriented engineer who enjoys building reliable data solutions and improving existing processes. You can understand a system’s current state, identify the desired outcome, and develop a logical plan to get there.

You are comfortable working with technical and non-technical stakeholders, asking the right questions, and explaining complex concepts clearly. You bring technical depth, business awareness, and a willingness to learn and contribute within a collaborative team.