Management Consultant

Our Client is seeking an IMT Management Consultant to lead and support enhancements, sustainment, and development of an Azure-based data management platform. The resource will contribute to defining technology roadmaps and implementing key data opportunities. The candidate will define the vision, roadmap, and execution strategy for an enterprise-scale data platform built on Azure and Databricks. Collaborating with Service Owners, Directors, and cross‑functional business stakeholders, the consultant will ensure platform capabilities, data products, and AI‑driven automation align with organizational objectives and long‑term strategies.

This role will oversee how data is ingested, governed, transformed, and delivered across the enterprise, driving consistency, scalability, and trusted data use for system integrations, analytics, reporting, operational decision‑making and AI workloads. As a strategic advisor, the consultant will also identify and introduce opportunities to use AI for accelerating data engineering, such as automated pipeline generation, metadata‑driven frameworks, and adaptive data quality. The consultant will bridge business priorities with technical execution, contributing to the future direction of the organization’s data ecosystem.

The ideal candidate will have hands‑on expertise in designing and implementing cloud‑native data architectures using Azure and Databricks. Responsibilities include architecting and building data lake environments using Delta Lake and Medallion architectures, as well as developing scalable ingestion and transformation pipelines using Databricks, Azure Data Factory, APIs, and integrations with platforms like ServiceNow and Talend. Expertise in cluster configuration, workflow orchestration, DataOps, schema management, and performance optimization is essential. The consultant will implement data quality frameworks, robust security models, and monitoring via Azure Monitor. Additionally, they will define reusable engineering frameworks and integration patterns to ensure secure, efficient, and scalable enterprise data operations.

Role is primarily remote, but the candidate must be available for on‑site meetings as required in downtown Edmonton. Meetings may occur up to 3–4 times (or more) per fiscal month, depending on the specific initiative and will be determined on an on‑demand basis. Must be a Canadian Citizen to apply and work within Canada at all times, due to network and security issues.

- Bachelor degree in Computer Science or related field of study.

- Certification in the Open Group Architecture Framework (TOGAF).

- Current advanced hands‑on engineering experience operating and optimizing Azure services, Azure Databricks environments, including cluster configuration, autoscaling strategies, security, Key Vault integration, encryption, CI/CD and SDLC/DataOps practices, monitoring/observability, capacity planning, and ensuring cost‑effective, high‑performing production workloads (4+ years).

- Current hands‑on design, development, and operation of end‑to‑end enterprise data pipelines using Databricks (PySpark/SQL notebooks, workflows, DLT), Azure Data Factory, APIs, Event Hubs, Functions, or related Azure services—including ingestion, transformation, validation, error handling, performance optimization, and production support (4+ years).

- Current hands‑on enterprise and solution architecture experience designing and implementing Azure‑based data platform architectures—covering compute models, integration patterns, identity/security models, network design, cost governance, and scalability—while collaborating closely with Cloud Engineering, Security, and Infrastructure teams (5+ years).

- Deep data architecture and Azure Databricks expertise with current production‑grade implementation of Medallion architecture, Delta Lake optimization, DLT/job orchestration, schema evolution, data quality frameworks, and expert‑level working knowledge of Unity Catalog permissions, governance, lineage, and secure data sharing across teams (4+ years).

- Demonstrated ability to work directly with senior leadership, including Service Owners, Service Directors, Executive Directors, and Architecture Review Boards—actively shaping data platform strategy, validating solution direction, and aligning architectural decisions with organizational priorities and enterprise technology standards (10+ years).

- Extensive systems integration experience with enterprise platforms such as ServiceNow using Talend, including hands‑on delivery of API‑based ingestion, incremental/CDC pipelines, metadata‑driven orchestration, event‑driven patterns, secure authentication, and full lifecycle integration aligned with enterprise governance and network standards (5+ years).

- Proven leadership mentoring data engineering and analytics teams by driving architectural best practices, reviewing solution designs, establishing coding and data engineering standards, and enabling teams to rapidly deliver high‑quality, scalable data solutions in a complex enterprise environment (5+ years).

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