AI & Data Analyst

Morgan Construction & Environmental Ltd•Edmonton, AB

12d•Onsite

About The Position

At Morgan, we don’t just build projects, we build careers and futures! Join us as an AI & DATA ANALYST and play a pivotal role in our dynamic world of heavy civil construction! We are looking for an AI & Data Analyst to partner with the Technology team in supporting multiple departments across the organization in leveraging AI integrations, automation, and data analytics to streamline operations, enhance decision-making, and deliver practical business solutions. This role will work closely with the AI Integration Specialist and the Chief Technology Officer (CTO), as well as stakeholders from various departments, to identify, design, and implement AI-enabled tools and automation workflows tailored to each department’s unique disciplines, processes, and business needs. The role is also responsible for helping to implement Large Language Model (LLM) solutions and for supporting the Azure infrastructure that underpins the organization’s AI models and architectures. The ideal candidate has strong analytical skills, a curiosity for emerging AI tools, and the ability to translate departmental requirements into pragmatic AI and automation solutions that create measurable value. This is an In-Office based position, Monday – Friday 8am-5pm, with an hour for lunch. It offers generous Vacation, personal and sick day entitlements.

Requirements

2–3 years of experience in data analytics, AI integration, automation, or a closely related field.
Bachelor’s degree in Data Analytics, Computer Science, Information Systems, Business Analytics, or a related field.
Demonstrated interest in and exposure to AI tools, large language models, and automation platforms.
Strong communication skills and the ability to explain data, automation, and AI concepts to non-technical users.
AI integration, adoption, and solution design.
LLM implementation (prompt engineering, RAG, embeddings, fine-tuning).
Azure AI infrastructure and architecture (Azure OpenAI, Azure AI Foundry, Azure ML, Azure AI Search).
Process automation and workflow design.
Data analysis, reporting, and visualization.
Python / SQL data analysis and scripting.
Advanced Excel.
Dashboard development and business intelligence.
Cross-functional collaboration across business and technology teams.
Business process analysis and improvement.
Change management and end-user enablement.
Critical thinking and translating business needs into technical solutions.

Nice To Haves

Experience implementing AI or automation solutions within a business environment.
Familiarity with AI platforms and tools such as OpenAI, Microsoft Copilot, Anthropic Claude, or similar.
Experience with workflow automation tools (e.g., Power Automate, n8n, Zapier, Make).
Knowledge of data visualization tools (Power BI, Tableau, or similar).
Exposure to AI-assisted coding tools, low-code/no-code platforms, and API integrations.
Experience working across multiple departments or disciplines to deliver technology solutions.
Understanding of data governance, privacy, and security best practices as they relate to AI deployments.
Experience with Azure AI services such as Azure OpenAI Service, Azure AI Foundry, Azure Machine Learning, Azure AI Search, or Azure Cognitive Services.
Experience designing and deploying AI architectures in Azure, including vector databases, RAG pipelines, and supporting services (storage, compute, networking, identity).
Familiarity with MLOps / LLMOps practices, including CI/CD pipelines, model monitoring, versioning, and cost optimization.
Relevant Microsoft certifications (e.g., AI-102, AZ-900, AZ-204, DP-100, and DP-700) are considered an asset.
Azure Fabric experience is a plus, and hands-on Azure ETL/Data Pipeline development experience is highly valued.

Responsibilities

Collaborate with the AI Integration Specialist to evaluate, design, and deploy AI-driven solutions tailored to the needs of multiple departments.
Partner with stakeholders across the organization to understand their workflows, pain points, and opportunities for AI-enabled improvements.
Research, recommend, and implement AI tools and platforms that deliver measurable business value.
Support departments in adopting AI solutions, ensuring implementations align with their unique disciplines, terminology, and operational requirements.
Develop proof-of-concept solutions to demonstrate the viability of AI use cases before full-scale rollout.
Implement, configure, and fine-tune Large Language Model (LLM) solutions, including context engineering, retrieval-augmented generation (RAG), embeddings, and integrations with internal data sources.
Evaluate and select appropriate LLM models and AI architectures based on business requirements, performance, and cost considerations.
Build, deploy, and maintain the Azure infrastructure required to support AI models, LLM workloads, and automation architectures.
Work with Azure AI services such as Azure OpenAI Service, Azure AI Foundry, Azure Machine Learning, Azure AI Search, and Azure Cognitive Services to support AI-powered solutions.
Provision and manage supporting Azure resources including storage, computing, networking, identity, and monitoring for AI workloads.
Apply best practices for AI solution architecture, including scalability, reliability, data security, privacy, and responsible AI principles.
Support MLOps and LLMOps practices, including model deployment pipelines, versioning, monitoring, and cost optimization, while applying CI/CD and ADevOps practices for cloud deployment using Azure Container Apps across the Azure environment.
Help automate repetitive, manual, and time-intensive processes across departments using AI tools, scripts, and workflow automation platforms.
Design, build, test, and maintain automation workflows that integrate with existing business systems and applications.
Assist in implementing AI-assisted forecasting, anomaly detection, summarization, and insight generation for a variety of business functions.
Continuously review processes to identify new opportunities for automation, efficiency gains, and error reduction.
Extract, transform, and analyze data from various departmental systems to support reporting, analytics, and decision-making.
Support data extraction, transformation, and loading (ETL) processes across business applications and analytics environments.
Ensure data accuracy, consistency, and integrity across reporting and analytics systems.
Build and maintain dashboards, reports, and data visualizations tailored to different departmental audiences.
Identify trends, anomalies, and actionable insights to support leadership and cross-functional decision-making.
Work closely with the AI Integration Specialist and the Chief Technology Officer (CTO) to align departmental initiatives with the broader technology and AI strategy.
Support cross-functional projects involving technology, operations, finance, human resources, and other business departments.
Assist in evaluating and implementing new technologies, reporting tools, and automation solutions across the organization.
Prepare documentation, training materials, and presentations to support end users, department leads, and leadership.
Act as a liaison between technical teams and business stakeholders, translating complex AI and data concepts into clear, accessible guidance.