Principal Data & AI Engineer

General Dynamics Mission Systems, Inc.; Ottawa; Presencial; CAD 120.000 - 150.000; Jornada completa

Descripción de la vacante

General Dynamics Mission Systems–Canada seeks a Principal Data & AI Engineer to establish and mature an enterprise data platform, defining architecture, and leading scalable data pipelines with Azure, Snowflake, and MuleSoft. You will guide data governance, security, and API strategies while enabling AI-enabled business processes and analytics across the enterprise.

You will drive real-time data processing, RAG adoption, and semantic data models, collaborating with stakeholders to deliver

Formación

• 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.

Responsabilidades

• 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.

Conocimientos

Data engineering

Cloud architecture

Data governance

SQL

Python

APIs

Observability

Educación

Bachelor's degree in CS/Engineering/Data Science or related field

Herramientas

MuleSoft

Snowflake

Azure

APIs

Descripción del empleo

GDMS-I is establishing an enterprise Data & AI capability to support digital transformation, advanced analytics, automation, and artificial intelligence initiatives across the organization.

As GDMS-I increases its investment in AI, a robust enterprise data foundation is required to ensure information is accessible, trusted, secure, and ready to support advanced analytics and AI-enabled business processes.

The Principal Data & AI Engineer will be responsible for establishing and maturing our enterprise data engineering capability, defining architecture and integration patterns, and leading the implementation of our strategic data platform. The role will lead the development of scalable data pipelines, integration frameworks, cloud-based data platforms, and AI data services that enable business intelligence, automation, and future AI capabilities across the enterprise.

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.

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.

Preferred

• 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.

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.