Location: 100% Remote anywhere in Canada

Duration: Full‑time

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.
- Solid 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.

📌 Data & AI Engineering Manager (Winnipeg)
🏢 Harvey Nash
📍 Winnipeg