Our client is seeking an experienced Principal Data & AI Engineer to help build and advance its enterprise data and artificial intelligence capabilities.

This is a senior, hands-on technical leadership opportunity for an engineer who enjoys designing complex data ecosystems, establishing scalable architecture, and turning enterprise data into a foundation for analytics, intelligent automation, and AI-driven innovation.

The successful candidate will play a pivotal role in shaping a modern data environment, connecting enterprise applications, improving data accessibility and reliability, and developing the technical infrastructure needed to support the organization's evolving AI strategy.

Unlike traditional data engineering positions focused primarily on pipeline development, this prospect combines enterprise architecture, platform engineering, systems integration, and emerging AI technologies.

What You'll Be Doing

Enterprise Data Platforms & Architecture

- Design and develop scalable enterprise data solutions using Microsoft Azure, Snowflake, and modern cloud technologies.
- Lead architectural decisions involving data lakes, cloud warehouses, integration layers, and analytical data models.
- Build reusable engineering frameworks that improve data accessibility, reliability, security, and performance.
- Establish technical standards and engineering practices to support sustainable platform growth.

Data Engineering & Systems Integration

- Develop and optimize data ingestion, transformation, and orchestration workflows across multiple enterprise applications.
- Design API-led integration solutions using MuleSoft and other integration technologies.
- Enable seamless information exchange between operational systems, engineering applications, and cloud platforms.
- Explore and implement event-driven architectures and real-time data processing where business requirements demand them.

AI Readiness & Intelligent Data Solutions

- Develop the data foundations required for machine learning, generative AI, and enterprise automation.
- Support advanced AI solutions involving Retrieval-Augmented Generation (RAG), vector databases, and enterprise knowledge retrieval.
- Integrate structured and unstructured information to support AI-powered applications and decision-making.
- Partner with technical stakeholders to translate AI opportunities into scalable engineering solutions.

Data Quality,



Governance & Reliability

- Implement engineering practices that promote data integrity, traceability, security, and operational resilience.
- Establish platform monitoring, observability, metadata management, and data quality controls.
- Incorporate governance requirements into architecture and integration designs.
- Ensure enterprise data services remain maintainable, performant, and scalable.

Technical Leadership & Strategic Delivery

- Serve as a senior technical authority for enterprise data architecture and AI-enabling technologies.
- Help shape platform priorities, technical roadmaps, and long-term engineering decisions.
- Work closely with solution architects, application development teams, business leaders, and external technology partners.
- Take ownership of complex technical initiatives from architecture and proof of concept through implementation and optimization.
- Balance strategic thinking with hands-on engineering and delivery.

What We're Looking For

- 8+ years of professional experience spanning data engineering, software development, enterprise integration, or related disciplines.
- Proven experience designing or modernizing enterprise-scale data environments.
- Strong technical knowledge of Microsoft Azure, particularly cloud-based data and analytics services.
- Practical experience building, integrating, or maintaining solutions using Snowflake.
- Experience with MuleSoft, API management, or comparable enterprise integration frameworks.
- Advanced proficiency with SQL, Python, and modern data engineering workflows.
- Strong understanding of data architecture, ETL/ELT patterns, data modeling, orchestration, and integration design.
- Familiarity with enterprise data governance, security, metadata, and quality management.
- Exposure to data platforms supporting business intelligence, advanced analytics, machine learning, or AI applications.
- Ability to independently architect solutions while remaining actively involved in engineering and implementation.




- Bachelor's degree in a relevant technical field or equivalent professional experience.

Additional Experience That Would Be Valuable

- Microsoft Fabric, Azure Data Factory, Azure Synapse Analytics, or similar cloud data services.
- Azure AI services, Azure OpenAI, or enterprise generative AI implementations.
- RAG solutions, vector search technologies, large language models, or AI agent frameworks.
- Data cataloging, master data management, and enterprise information governance.
- Experience contributing to enterprise-wide technology transformation initiatives.

Why Consider This Opportunity?

This position offers the opportunity to influence the direction of an organization's enterprise data and AI ecosystem at a foundational stage.

Rather than simply maintaining an established platform, you'll have the opportunity to shape architecture, introduce engineering standards, and build capabilities that support future AI innovation.

It's particularly well suited to a senior engineer or architect who wants meaningful technical ownership, broad enterprise exposure, and the opportunity to remain hands-on with modern data technologies.

About iSource Professionals

iSource Professionals specializes in connecting organizations with experienced Cybersecurity, Data, AI, and Digital Technology professionals.

Our recruitment approach combines targeted technical sourcing with practitioner-led candidate assessments to identify professionals who bring both technical depth and practical delivery experience.

Pay: $150,000.00-$180,000.00 per year

Benefits:

- Dental care
- Extended health care

Experience:

- Senior Data Engineer: 8 years (preferred)
- AI Readiness & Intelligent Data Solutions: 3 years (preferred)
- Microsoft Azure: 5 years (preferred)
- MuleSoft, API management: 6 years (preferred)
- Snowflake: 6 years (preferred)
- Machine Learning, AI, RAG: 5 years (preferred)
- Advanced proficiency with SQL, Python: 8 years (preferred)
- Data Architecture, ETL/ELT: 8 years (preferred)
- AI Agent Frameworks: 2 years (preferred)
- Microsoft Fabric, Azure Data Factory, Synapse Analytics: 2 years (preferred)
- Enterprise Integration: 8 years (preferred)
- designing or modernizing enterprise-scale data environments: 8 years (preferred)

Location:

- Ottawa, ON (required)

Work Location: Hybrid remote in Ottawa, ON

📌 Principal Data and AI Engineer (Ottawa)
🏢 iSource Professionals
📍 Ottawa