Summary
✨ AI‑Generated
Join a data and AI consulting team as an experienced Data Engineering Consultant. You will design and deliver modern data platforms, pipelines, and AI-ready data solutions using cloud technologies, while working directly with stakeholders to clarify requirements, structure complex problems, recommend practical approaches, and guide implementations from discovery through adoption. The engagement is initially five months with potential for extension and supports remote or hybrid work.
Highlights
Five-month consulting engagement with possible extension, offering hands-on work on modern data platforms, cloud technologies, and AI-ready solutions while partnering directly with clients on complex business and technology challenges.
Description
Data Engineering Consultant - Data & AI practice
Contract length: 5 months (with the possibility of extension)
Work location: Canada, Remote / Hybrid
Eligible for Secret level security clearance
We are seeking an experienced and client-focused Data Engineering Consultant to join our Data & AI practice.
You will help clients solve complex business and technology challenges by designing and delivering modern data platforms, pipelines, and AI-ready data products using Microsoft Fabric, Azure Databricks, Python, and the broader Azure ecosystem.
This role combines hands-on engineering with consulting.
You will work directly with client stakeholders, clarify ambiguous requirements, structure problems, recommend practical solutions, and guide delivery from discovery through implementation and adoption.
What You'll Do
Partner with client stakeholders to understand business priorities, uncover root causes, define requirements, and translate complex needs into actionable data solutions.
Lead problem-solving activities across ambiguous and complex environments, evaluating options, risks, dependencies, and trade-offs.
Design, build, test, and support scalable data pipelines, lakehouse solutions, and curated data products using Microsoft Fabric and Azure Databricks.
Develop reliable data transformations and engineering components using Python, PySpark, and SQL.
Facilitate discovery sessions, technical workshops, backlog refinement, solution walkthroughs, and stakeholder updates.
Manage stakeholder expectations through clear communication, proactive issue management, and transparent delivery reporting.
Apply sound engineering practices for data quality, observability, security, governance, performance optimization, and operational support.
Contribute to architecture decisions, estimates, delivery plans, technical documentation, and client presentations.
Collaborate with architects, analysts, data scientists, AI engineers, and delivery teams across onshore and offshore environments.
Support and mentor junior team members through technical guidance, reviews, and knowledge sharing.
Explore opportunities to integrate AI engineering capabilities into data solutions, including Microsoft Foundry and Microsoft Copilot Studio.
Required Qualifications
Strong experience in data engineering, analytics engineering, business intelligence, or related data roles.
Hands-on experience delivering solutions with both Microsoft Fabric and Azure Databricks.
Strong programming skills in Python, with practical experience using PySpark and SQL.
Experience designing and building ETL/ELT pipelines, lakehouse architectures, data transformations, and curated data layers.
Proven consulting or professional services experience, including direct interaction with client stakeholders.
Demonstrated ability to structure complex problems, investigate root causes, evaluate alternatives, and drive pragmatic solutions.
Strong stakeholder management, facilitation, communication, and presentation skills.
Ability to explain technical concepts to both technical and non-technical audiences.
Experience with Azure Data Factory, Azure Data Lake Storage, Power BI, Microsoft Purview, or Azure DevOps.
Experience working in Agile delivery environments and contributing to estimation, planning, testing, and release activities.
AI Engineering Exposure
Exposure to AI engineering concepts and the delivery of AI-enabled or agentic solutions.
Familiarity with Microsoft Foundry for developing, evaluating, or operationalizing AI solutions.
Familiarity with Microsoft Copilot Studio for building and integrating copilots or agents into business workflows.
Understanding of how governed, high-quality data platforms enable analytics, machine learning, generative AI, and agentic experiences.
