Position Overview The Data Engineer is responsible for the design, development, and ongoing evolution of the organization’s data platform, integration capabilities, and foundational data infrastructure. This role plays a key part in the organization’s broader technology modernization and data strategy initiatives. Working within the IT department, the Data Engineer will support the integration and flow of information across business systems, applications, and data sources to improve operational efficiency and organizational decision-making. The role combines hands-on implementation and delivery with longer-term platform and data capability development, including building and maintaining data pipelines, supporting data warehousing initiatives, and enabling business intelligence and analytics capabilities across the organization. The Data Engineer will collaborate with leadership, technical staff, vendors, and business partners to help establish scalable and sustainable data capabilities. The role will also help drive the organization’s exploration, evaluation, and adoption of practical AI-enabled solutions and related technologies. This role is well suited to a pragmatic, self-directed technology professional who enjoys building foundational systems, solving complex integration and data challenges, and helping organizations modernize their technology capabilities. Key Responsibilities Data Platform & Integration Development Designs, develops, implements, and maintains data pipelines, integrations, and workflows across organizational systems and applications. Supports the development and ongoing evolution of the organization’s data warehouse and related data platform capabilities. Develops and maintains processes that improve the accessibility, reliability, and usability of organizational data. Supports integration efforts between CRM, ERP, business applications, cloud platforms, databases, APIs, and related systems. Monitors, troubleshoots, and optimizes data flows, integrations, and platform performance. Collaborates with vendors and technical teams to support system integrations, upgrades, and platform enhancements. Evaluates and recommends modern data technologies, tools, and architectural approaches that align with organizational goals and operational needs. Participates in platform, tooling, and architectural discussions related to the organization’s evolving data strategy. Data Management & Analytics Enablement Supports the organization’s reporting, analytics, and business intelligence capabilities through the delivery of reliable and well-structured data solutions. Develops and maintains data models, transformations, and supporting structures used for analytics, reporting, and operational insights. Supports the improvement of data quality, consistency, and reliability across systems and integrations. Assists with the preparation of datasets, reports, dashboards, and data extracts to support operational and strategic decision-making. Collaborates with interest holders to identify opportunities for workflow automation, process improvement, and operational efficiencies enabled through improved data capabilities. Supports the establishment of foundational practices related to data management, documentation, and sustainable platform operations. AI & Emerging Technology Support Helps drive the organization’s exploration, evaluation, and adoption of practical AI-enabled solutions and related technologies. Identifies opportunities where AI, automation, or modern data capabilities may improve organizational effectiveness or service delivery. Collaborates with leadership and technical teams to support experimentation, evaluation, and implementation of emerging technology solutions. Organizational Support Works collaboratively with leadership, staff, vendors, and affected parties across the organization to support technology modernization initiatives. Provides technical guidance and recommendations related to data architecture, integrations, platforms, and operational sustainability. Prepares and maintains technical documentation related to integrations, data flows, configurations, standards, and operational procedures. Supports cross-departmental projects and may be assigned work from other departments as required. Performs other related duties as assigned. Qualifications The successful applicant must have: A diploma or degree in Computer Science, Information Systems, Software Engineering, Data Engineering, or a related field, and 5 years' experience in that field, or an equivalent combination of education, training, and practical experience. Experience designing, developing, and supporting data pipelines, integrations, and data platform solutions in cloud or hybrid environments. Experience working with modern data engineering, analytics engineering, software engineering, or related technical practices. Experience with databases, SQL, APIs, scripting, and data transformation technologies. Experience supporting or developing data warehouse, reporting, analytics, or business intelligence solutions. Experience working with cloud platforms, SaaS applications, and system integrations. Experience evaluating and implementing modern data tools, platforms, or architectural approaches is considered an asset. Familiarity with technologies such as AWS, Tableau, integration platforms, CRM systems, ERP systems, or modern cloud data tooling is considered an asset. Understanding of data quality, operational sustainability, maintainability, and scalable solution design principles. Ability to balance hands-on delivery work with longer-term planning and continuous improvement initiatives. Strong analytical and problem-solving skills, with the ability to evaluate complex technical and operational challenges. Ability to work independently, exercise sound judgment, and operate effectively in a collaborative team-oriented environment. Strong communication and relationship-building skills, with the ability to work effectively with both technical and non-technical partners. Strong organizational and time management skills, with the ability to manage competing priorities in a dynamic environment. Demonstrated curiosity, continuous learning mindset, and interest in emerging technologies and modern data practices.