An established organization seeking a Director, Enterprise Data & Integration to lead the evolution of its enterprise-wide data and integration capabilities.

This is a senior technology leadership opportunity for an individual who can bring structure, direction, and scalability to an evolving data environment.

The successful candidate will be responsible for developing an enterprise data strategy, establishing architectural and governance standards, and helping the organization transition from independently managed data initiatives toward a more connected, reliable, and strategically aligned ecosystem.

Working closely with executive leadership and cross-functional technology teams, this individual will play an important role in strengthening the organization's data foundations to support business intelligence, operational efficiency, automation, and emerging artificial intelligence capabilities.

This position combines strategic leadership, enterprise architecture, technology governance, and team development.

Key Areas of Responsibility

Enterprise Data Strategy & Transformation

- Define a long-term vision and practical roadmap for enterprise data management, integration, and modernization.
- Develop the operating structures, technical capabilities, and governance practices needed to support an enterprise-wide data function.
- Align data investments and architecture decisions with organizational priorities and digital transformation objectives.
- Identify opportunities to improve how information is collected, connected, managed, and used across business functions.
- Establish a sustainable approach to treating enterprise information as a shared organizational asset.

Data Architecture & Integration Leadership

- Provide architectural oversight for enterprise data ecosystems, integration frameworks, and information management practices.
- Establish consistent approaches to API management, reusable integration services, data pipelines, and event-driven architectures.
- Guide the adoption and governance of enterprise integration technologies, including MuleSoft or comparable platforms.
- Define standards for data modeling, metadata, lineage, master data, and information quality.
- Reduce reliance on fragmented integrations, inconsistent data structures, and isolated technology solutions.
- Ensure enterprise architecture decisions support security, scalability, resilience, and regulatory obligations.

Cloud Platforms, Analytics & AI Readiness

- Guide the strategic direction of cloud-based data platforms, analytics environments, and integration technologies.
- Support the evolution of modern data capabilities using technologies such as Snowflake, Microsoft Azure, Microsoft Fabric, Databricks, or similar platforms.
- Partner with technology and business stakeholders to establish trusted data foundations for reporting, advanced analytics, machine learning, and AI initiatives.




- Assess emerging technologies and recommend investments that deliver sustainable business value.
- Encourage platform simplification, interoperability, and the reuse of enterprise data services.

Technology Leadership & Team Development

- Build, mentor, and provide technical direction to a developing Data Engineering team.
- Establish clear engineering practices, accountability, and technical delivery expectations.
- Work collaboratively with enterprise architects, cybersecurity teams, application development, infrastructure, and business leaders.
- Support resource planning, initiative prioritization, and execution of enterprise data programs.
- Communicate technical strategy, architectural trade-offs, and investment recommendations to senior leadership.
- Balance long-term architectural objectives with immediate operational and business requirements.

Governance, Standards & Continuous Improvement

- Introduce practical governance models that support consistent technology decisions and responsible data management.
- Establish architecture review processes, technical standards, and reusable design patterns.
- Strengthen data quality, security, access controls, and lifecycle management.
- Identify technical debt and integration inefficiencies while developing realistic modernization priorities.
- Promote ongoing improvements in platform reliability, engineering maturity, and enterprise data accessibility.

What You'll Bring

Required Experience & Qualifications

- 10+ years of progressive experience in enterprise data architecture, data engineering, integration architecture, enterprise architecture, or related technology disciplines.
- Demonstrated success developing or advancing enterprise data strategies, architecture standards, governance frameworks, and technology roadmaps.
- Experience leading technical professionals and developing engineering capabilities.
- Solid understanding of enterprise data management, information architecture, cloud technologies, integration patterns, and governance principles.
- Ability to engage and influence senior technology and business stakeholders.
- Experience guiding complex technology initiatives involving multiple systems, teams, and organizational priorities.
- Familiarity with AI and machine learning concepts and their enterprise data requirements.
- Strong communication, strategic planning, and technical decision-making skills.
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related discipline, or equivalent professional experience.

Additional Experience That Would Be Valuable

- Enterprise integration architecture using MuleSoft Anypoint Platform,



including API-led connectivity and integration governance.
- Experience with Snowflake, Microsoft Fabric, Azure Data Factory, Azure Synapse Analytics, Databricks, Microsoft Purview, or AWS data technologies.
- Exposure to enterprise analytics modernization, intelligent automation, and AI/ML enablement.
- Knowledge of data governance, master data management, metadata management, and information lifecycle practices.
- Familiarity with established architecture or IT governance frameworks such as TOGAF, DAMA-DMBOK, COBIT, or ITIL.
- Experience introducing enterprise-wide data standards within complex, multi-stakeholder environments.

Security & Employment Requirements

Due to the nature of the organization's operations, the successful candidate must be eligible to work in Canada and meet applicable personnel security screening requirements.

The position requires the ability to obtain and maintain a Canadian government security clearance. Additional screening or access requirements may apply depending on project responsibilities and regulatory obligations.

Compensation & Career Opportunity

The position also offers eligibility for a management incentive plan and a competitive employee benefits package.

Final compensation will reflect the successful candidate's experience, technical expertise, leadership capabilities, and overall alignment with the role.

Why Consider This Opportunity?

- Enterprise-wide influence: Help shape how data is managed, integrated, and used across a complex organization.
- Build and lead: Develop an emerging data engineering capability and establish sustainable engineering practices.
- Strategic ownership: Influence architecture decisions, technology investments, and the long-term data roadmap.
- Modern technology landscape: Work with enterprise cloud platforms, integration technologies, advanced analytics, and AI-enabling solutions.
- Executive visibility: Collaborate directly with senior technology leadership and contribute to major transformation priorities.

This opportunity is particularly well suited to an experienced Data Architecture Leader, Head of Enterprise Data, or Data & Integration Director who enjoys building capabilities, influencing strategy, and developing high-performing technical teams.

Pay: $170,000.00-$190,000.00 per year

Benefits:

- Dental care
- Extended health care
- Vision care

Experience:

- Enterprise Data Architecture: 10 years (preferred)
- Integration Architecture: 10 years (preferred)
- lead technical team and developing engineering capabilities: 7 years (preferred)
- AI and Machine Learning concepts, data requirements: 5 years (preferred)
- Data Management: 10 years (preferred)
- MuleSoft Anypoint Platform: 3 years (preferred)
- Snowflake: 3 years (preferred)
- AWS data technologies: 3 years (preferred)
- AI/ML enablement: 1 year (preferred)

Location:

- Ottawa, ON (required)

Work Location: Hybrid remote in Ottawa, ON

📌 Director, Enterprise Data & Integration (Ottawa)
🏢 iSource Professionals
📍 Ottawa