Data & AI Engineering Manager

Harvey Nash; Canada; Remote; CAD 100,000 - 130,000; Full time

Job summary

A leading technology consultancy is seeking a Data & AI Engineering Manager to lead teams in building scalable data and AI products in a SaaS environment. The role combines technical leadership and people management, emphasizing AI capabilities and data excellence. Candidates should have 6+ years in software engineering, including 2+ in management, alongside experience with Python, Databricks, Azure, and Kubernetes. This remote role in Canada focuses on driving innovation and fostering a high-trust culture.

Qualifications

• 6+ years of software engineering experience, including 2+ years in a direct people management role.
• 3–5 years of experience working on Data and/or AI Engineering teams.
• Strong experience building modern SaaS data products using Python, Databricks, Azure, and Kubernetes.
• Proven expertise with Data Lakehouse architectures and data governance.
• Solid understanding of Data Science concepts, including Machine Learning.

Responsibilities

• Lead, mentor, and develop a team of Data and/or AI Engineers.
• Drive the design and evolution of scalable data and AI architectures.
• Oversee the development of customer-facing data products.
• Guide teams through complex system design and data governance.
• Champion modern AI practices, including Machine Learning and Generative AI.

Skills

Software engineering experience

People management

Data and/or AI Engineering

Python

Databricks

Azure

Kubernetes

Data governance

Machine Learning

Generative AI

Agile mindset

Tools

Databricks

Apache Spark

Azure

Kubernetes

Job description

Location: 100% Remote anywhere in Canada

Duration: Full‑time

Job Description

Role Overview

We are seeking an Data & AI Engineering Manager to lead high‑impact teams building scalable, customer‑facing data and AI products in a modern SaaS environment. This role blends hands‑on technical leadership, people management, and architectural ownership, with a strong emphasis on AI‑driven capabilities and data platform excellence.

You will guide engineers through technical complexity, foster a high‑trust and people‑first culture, and partner closely with product, data science, and platform teams to deliver reliable, secure, and scalable solutions.

Key Responsibilities

• Lead, mentor, and develop a team of Data and/or AI Engineers, providing clear technical direction, career coaching, and performance feedback.
• Drive the design and evolution of scalable data and AI architectures, leveraging technologies such as Databricks, Apache Spark, Azure, and Kubernetes.
• Oversee the development of customer‑facing data products, ensuring reliability, performance, and strong engineering standards.
• Guide teams through complex system design, data governance, and platform decisions, emphasizing reusable, maintainable architectures.
• Partner cross‑functionally with Product, Data Science, and Platform teams to align technical solutions with business and customer needs.
• Champion modern AI practices, including Machine Learning, Generative AI, RAG architectures, and agentic frameworks.
• Foster a culture of accountability, autonomy, and continuous improvement in a fast‑paced, agile environment.
• Clearly communicate technical strategy, trade‑offs, and outcomes to both technical and non‑technical stakeholders.

Required Qualifications

• 6+ years of software engineering experience, including 2+ years in a direct people management role.
• 3–5 years of experience working on Data and/or AI Engineering teams.
• Strong experience building modern SaaS data products using Python, Databricks, Azure, and Kubernetes.
• Proven expertise with Data Lakehouse architectures, Apache Spark, software design principles, and data governance.
• Solid understanding of Data Science concepts, including Machine Learning and Generative AI.
• Demonstrated ability to lead with empathy, accountability, and a people‑first mindset in autonomous environments.
• Exceptional communication skills, with the ability to translate complex technical concepts into clear, actionable insights.

Preferred Qualifications

• Experience or strong interest in FinTech and regulated environments.
• Strong Agile and DevOps mindset, with experience driving continuous delivery and operational excellence.
• Exposure to AI technologies beyond traditional ML, including Generative AI, RAG, and agentic AI frameworks.