JOB DESCRIPTION
Job Description
Job Title: Senior Data Engineer
Location: Hybrid – 2-3 days in the Toronto office
Note: Only candidates whose experience closely matches the requirements will be contacted
About Our Client
Our client is a fast-moving, innovation-driven team at the forefront of artificial intelligence based in Toronto, embedded in Canada's thriving AI ecosystem.
They specialize in transforming ambitious concepts into high-impact, real-world solutions.
Their work spans intelligent automation, strategic forecasting, and agentic platforms that streamline complex workflows and unlock business value.
From rapid prototyping to consortium-led initiatives, they are shaping the future of procurement and decision intelligence.
Join them to be part of a team that values speed, creativity, and purpose—delivering AI that matters.
Who You Are and What You'll Do
We are seeking an experienced Senior Data Engineer to join our client's team and play a pivotal role in building and managing large-scale data pipelines, with a focus on supporting the development of Large Language Models (LLMs) and agent-based applications.
In addition to your technical expertise, you will manage and mentor junior data engineers, helping them grow while ensuring high standards of data engineering practices across the team.
Responsibilities:
• Lead and Manage: Oversee the work of junior data engineers, providing mentorship and guidance to drive the successful execution of projects.
• Develop Data Pipelines: Design and implement scalable and reliable data pipelines to handle increasing data complexity and volume for LLM and agent applications.
• LLM & GenAI Application Support: Develop and optimize data infrastructures to meet the needs of predictive modeling, machine learning, and generative AI applications.
• Collaborate Across Teams: Work closely with data scientists, machine learning engineers, and business stakeholders to understand data requirements and deliver high-quality data solutions.
• Data Integration: Extract, transform, and load (ETL) large datasets from a variety of structured and unstructured data sources using APIs and other technologies.
• Documentation & Best Practices: Create and maintain clear, concise technical documentation for data engineering workflows, pipelines, and processes.
• Mentorship & Growth: Foster a collaborative environment by mentoring junior team members in best practices, new technologies, and approaches in data engineering.
Qualifications:
• Bachelor's degree in computer science, engineering, or a related field.
Advanced degree is a plus.
• 5+ years of experience in data engineering or related roles, with at least 2 years of experience working with LLMs, agent-based applications, or similar advanced machine learning technologies.
• Proficiency in Data Engineering Technologies: Advanced skills in SQL, Python, and ETL frameworks for building data pipelines.
• Experience with APIs & Data Integration: Strong experience in working with APIs to extract, transform, and load data from multiple sources, including structured and unstructured data formats (e.g., JSON, XML).
• Machine Learning & AI Expertise: Familiarity with machine learning models, including large language models (LLMs) and generative AI techniques, and an understanding of how to build and optimize data pipelines to support these applications.
• Data Storage & Modeling: In-depth knowledge of data modeling and storage solutions for both structured and unstructured data, as well as cloud data technologies like Google BigQuery and Azure Data Lake.
• Leadership & Communication Skills: Strong leadership abilities to mentor and lead junior engineers.
Excellent communication and collaboration skills to work cross-functionally with teams.
• Problem Solving: Proven ability to address complex data challenges, with a strong focus on data optimization, performance, and quality assurance.
