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Principal Data & AI Engineer

General Dynamics Mission Systems
Ottawa, CAN
Full-time
Senior · 8+ years experience
Hybrid
CAD 140000-170000 / year
Discovered 1 weeks ago
azureazure-data-factoryopenaipythonsnowflakesql

Full Job Posting

Key Responsibilities

  • Establish and oversee enterprise data platforms leveraging Microsoft Azure, Snowflake, and MuleSoft.
  • Define the strategy for scalable, reusable, and governed data pipelines for ingesting, transforming, and integrating enterprise data from business systems, engineering platforms, and external sources.
  • Architect the enterprise integration services and APIs using MuleSoft and modern integration patterns.
  • Lead the implementation of cloud-native data architectures, including data lakes, data warehouses, and semantic data models.
  • Establish data engineering standards, design patterns, and best practices to support enterprise scalability and long-term sustainability.
  • Manage the prioritization of data products that enable business intelligence, reporting, analytics, automation, and AI initiatives.
  • Enable AI and machine learning use cases by ensuring high-quality, accessible, and governed enterprise data.
  • Direct the adoption of Retrieval-Augmented Generation (RAG), vector search, knowledge retrieval, and AI integration capabilities where appropriate.
  • Define the direction for and manage real-time and event-driven data processing solutions.
  • Establish requirements and oversight for monitoring, observability, data quality, metadata management, and governance controls across enterprise data platforms.
  • Collaborate with business stakeholders, application teams, architects, and technology partners to identify and deliver data solutions that address business priorities.
  • Lead the development and execution of GDMS-I's enterprise Data & AI strategy and roadmap.
  • Preferred
  • It is a requirement that General Dynamics Mission Systems–Canada be registered with the Canadian Controlled Goods Program and that all of its workforce be security assessed. Successful applicants must meet all applicable security requirements, including but not limited to the ability to obtain and maintain a Canadian government security clearance. Applicants may be required to meet additional security requirements in order to gain access to technical data, classified areas, or information that is subject to international regulations. You must be eligible to work in Canada.
  • The hiring range for this position is $140,000 - $170,000 CAD annually. This role is eligible for a management incentive plan. Our goal is to provide a fair and competitive offer based on an assessment of internal equity and your qualifications, including:
  • Relevant experience
  • Technical and non-technical skills
  • Education and certifications

Qualifications

  • Bachelor’s degree in computer science, Engineering, Data Science, Information Systems, or related discipline, or demonstrable equivalency in experience.
  • 8+ years of experience in data engineering, systems integration, software engineering, or related technical disciplines.
  • Demonstrated experience establishing and maturing enterprise-scale data platforms and integration solutions.
  • Strong experience with Azure cloud services, including data, analytics, and AI-related services.
  • Experience developing and supporting Snowflake-based data platforms.
  • Hands-on experience with MuleSoft or equivalent enterprise integration platforms.
  • Strong development experience with SQL, Python, APIs, and data orchestration technologies.
  • Strong understanding of data architecture, data modeling, data governance, security, and metadata management.
  • Experience supporting analytics, reporting, machine learning, or AI-enabled solutions.
  • Ability to operate independently in a highly technical, hands-on engineering role.
  • Experience with Microsoft Fabric, Azure Data Factory, Synapse Analytics, Azure AI, Azure OpenAI, and related Microsoft data services.
  • Experience implementing RAG architectures, vector databases, AI agent frameworks, and large language model integrations.
  • Experience with data cataloging, master data management, and enterprise information governance.

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