Data & AI Engineer, Business Intelligence

CBC/Radio-Canada•Toronto, ON

1d•Hybrid

About The Position

The Business Intelligence team’s data engineers are strategic partners and catalysts, providing data-as-a-service to support product, content, and operational decision-making across the organization. To support our expanding AI practice, we are seeking a Data & AI Engineer to scale the robust data foundations required for GenAI and machine learning initiatives. In this role, you will be a key contributor to our AI roadmap, responsible for maintaining our Azure Databricks platform, architecting new ETL/ELT pipelines, and developing the data-centric solutions that power GenAI applications. You will work within a high-performing, cross-functional team to ensure our data lake is optimized to serve as the backbone for the next generation of AI-driven business solutions and automated organizational workflows. We are open to qualified candidates located within Canada with work authorization, but the CBC’s BI team is based in Toronto.

Requirements

5+ years of experience in Big Data Engineering, specifically handling high-volume clickstream or event data
Experience architecting robust data models optimized for downstream data analysis and AI/ML applications
Deep experience in enforcing data quality and governance
Experience building data pipelines that support LLM applications, such as RAG or vector-based search
Experience integrating LLMs into workflows to automate business processes
Deep experience with the Azure ecosystem, specifically Azure Databricks, EventHub, ADLS Gen2, and Azure DevOps
Proficiency in Python (PySpark) and SQL for large-scale, distributed data processing
Experience with workflow automation tools, specifically Apache Airflow
Solid understanding of distributed computing and big data best practices using Spark
Experience handling structured, semi-structured, and unstructured data in both batch and streaming contexts
Thrive in an autonomous and ambiguous environment that rejects “business as usual.”
Enjoy working with people and sharing your knowledge with them in a collaborative way
Approach things with a beginner’s mind and are constantly curious and learning
Skilled at presenting ideas to non-technical stakeholders and management
Know how to listen and empathize with others
Fluent in English and are an excellent verbal and written communicator
Qualified candidates will be subject to a practical assessment of the above requirements

Nice To Haves

Working knowledge of French or willingness to learn/advance communication skills in French
Experience with Agentic AI solution architecture
Experience with LLMOps
Data or AI engineering certification in any of the three major cloud platforms (preferably Azure)
Experience with Continuous Integration / Continuous Deployment (CI/CD) pipelines
Experience with project management and support tools such as JIRA and Confluence

Responsibilities

Maintaining our Azure Databricks platform
Architecting new ETL/ELT pipelines
Developing the data-centric solutions that power GenAI applications
Ensuring our data lake is optimized to serve as the backbone for the next generation of AI-driven business solutions and automated organizational workflows
Ingesting and transforming diverse data sources specifically for AI initiatives, ensuring data readiness for LLMs and agentic workflows
Working alongside counterparts at Radio-Canada to align data strategies

Benefits

Hybrid work environment with flexible work schedules
Enrollment in a generous defined benefits pension plan
Competitive total rewards package
20% of time for innovation, learning and development
Opportunities to work with cutting edge technology
Opportunities for continued learning and professional development
Opportunities to become a member of our Employee Resource Groups
Pair programming and mentorship opportunities
A creative and dynamic work environment
A supportive management team committed to upholding the highest standards of diversity and inclusivity
An environment which favours experimentation and an iterative approach in order to achieve the highest form of technical innovation