Data Manager / Data Architecture Manager

DT Global•Ottawa, ON

7d•Hybrid

About The Position

DT Global is seeking a strategic and forward-thinking Data Manager / Data Architecture Manager to lead the development of our enterprise-wide data strategy, architecture, governance, analytics and AI enablement capabilities. Reporting to the IT Business & Data Systems Manager, this role will play a pivotal part in transforming how DT Global leverages data across programs, operations and corporate functions. You will drive the integration of diverse data sources into a unified data ecosystem, enabling evidence-based decision-making, improved operational efficiency, enhanced donor reporting, and greater development impact. The role is centred on strategy, architecture and business enablement rather than hands-on technical development.

Requirements

Degree qualification in Data Science, Computer Science, Information Systems, Engineering, Statistics or a related discipline.
8–12 years’ experience in data management, data strategy, analytics or enterprise data architecture roles.
Demonstrated experience designing and implementing enterprise data ecosystems and integration strategies.
Experience delivering analytics platforms, reporting solutions or AI-enabled business initiatives.
Strong understanding of data governance, data quality, metadata and information management practices.
Knowledge of enterprise data architecture, cloud data ecosystems and modern data platforms.
Ability to influence senior stakeholders and communicate complex concepts in business terms.
Excellent stakeholder management, communication and change management skills.

Nice To Haves

Experience within international development, donor-funded programs, NGOs or complex global organisations.
Familiarity with ITIL and enterprise service management frameworks.
Understanding of emerging AI technologies and practical business applications of generative AI.

Responsibilities

Lead the development and implementation of DT Global’s Data Strategy and roadmap.
Define and maintain enterprise data architecture principles, standards and governance frameworks.
Establish a unified data ecosystem spanning data sourcing, integration, storage, transformation, analytics and applications.
Drive integration across disparate systems to create a consistent and trusted data environment.
Partner with IT and enterprise architecture teams to ensure scalability, security and sustainability.
Identify, prioritise and oversee enterprise analytics and AI use cases.
Support the delivery of dashboards, reporting solutions and analytical tools that improve decision-making.
Champion the adoption of AI and generative AI solutions for knowledge management, reporting and operational effectiveness.
Develop business cases, measure value realisation and promote adoption of data-driven initiatives.
Establish enterprise-wide governance frameworks covering data quality, ownership, stewardship and lifecycle management.
Improve data transparency, lineage, consistency and auditability across the organisation.
Develop policies and guidance for the responsible and ethical use of AI.
Collaborate with Risk, Compliance and HR teams to ensure governance requirements are met.
Act as a trusted advisor to senior leaders on data, analytics and AI opportunities.
Bridge technical and business stakeholders to translate strategic needs into actionable initiatives.
Promote data literacy and a data-driven culture across global teams and country programs.
Support organisational capability building in analytics, AI awareness and responsible AI adoption.