Data Engineer

AI is automating routine ETL logic and data quality checks, reducing the need for manual pipeline coding. Generative AI tools like GitHub Copilot and AI-assisted data profiling are speeding up schema discovery and documentation but still require human oversight for complex transformations. The role is shifting from 'building pipes' to 'managing data products and AI training pipelines,' which raises the bar for understanding ML workflows. However, demand for data engineers to curate and prepare high-quality training data for AI models is growing, creating new opportunities particularly in Canada's burgeoning AI hubs (Toronto, Montreal, Vancouver).