Data and AI Enablement Specialist(Business Analyst)

TEEMA; Edmonton; On-site; CAD 65,000 - 90,000; Full time

Job summary

TEEMA is seeking a Data & AI Enablement Analyst to drive adoption and usability of data, analytics, and AI solutions across the organization. The role sits at the intersection of business, data, and technology, collaborating with stakeholders across Supply Chain, Finance, Marketing, Sales, and Information Systems to identify opportunities and improve data accessibility.

You will ensure data assets are discoverable, well-documented, and aligned with business needs while contributing to data

Qualifications

• 1-3 years of experience in BI, reporting, business analysis, data management, or related field.
• Strong communication skills to explain technical concepts to non-technical stakeholders.
• Excellent analytical and problem-solving abilities.
• Ability to distinguish between data issues, process issues, and business expectation gaps.
• Experience collaborating across business and technology teams.
• Strong organizational and time management skills in a fast-paced environment.
• Foundational understanding of data, analytics, reporting, and data governance concepts.

Responsibilities

• Partner with business stakeholders to identify opportunities for new data, analytics, and AI solutions.
• Help evaluate and prioritize use cases based on business impact and value.
• Act as a trusted resource for associates seeking data, reporting, or analytics support.
• Promote data literacy by helping users locate and leverage existing data assets and insights.
• Analyze requests and feedback to identify opportunities for process improvements and new analytics capabilities.
• Create and maintain knowledge base articles and documentation related to data, analytics, and AI assets.
• Improve discoverability and usability of data assets through clear business-friendly documentation.
• Support ongoing efforts to enhance AI-powered tools by ensuring accurate and well-maintained knowledge content.
• Contribute to data dictionaries, business definitions, metadata, and documentation standards.
• Monitor business-critical datasets and data pipelines to ensure availability and quality.
• Collaborate with business and technical teams to improve master data quality and consistency.
• Escalate data quality issues and support remediation efforts with stakeholders.
• Assist with testing and validation of new data and analytics assets before release.
• Maintain metadata, tagging structures, and data classification standards.
• Support data preparation for AI-enabled solutions, including Copilot, GenAI, retrieval-based systems.
• Assist with data classification and governance initiatives to manage sensitive information.
• Help identify and mitigate risks related to AI outputs, including hallucinations, bias, and misinformation.
• Participate in continuous improvement efforts for AI-enabled tools and solutions.
• Perform functional testing, sanity checks, and data quality validation on reporting, analytics, and AI assets.
• Verify delivered solutions meet business outcomes and user requirements.
• Support quality assurance activities across data and analytics initiatives.

Skills

Analytical thinking

Communication skills

Problem solving

Cross-functional collaboration

Time management

BI concepts

Education

Degree or diploma in Data Analytics / Information Systems / Computer Science

Tools

Azure Data Lake

Databricks

Microsoft Fabric

Dynamics 365 F&O data structures

Job description

Our client is looking for a Data & AI Enablement Analyst to help drive the adoption, usability, and effectiveness of data, analytics, and emerging AI solutions across the organization.

This role sits at the intersection of business, data, and technology, working closely with stakeholders across Supply Chain, Finance, Marketing, Sales, and Information Systems to identify opportunities, improve data accessibility, and support the organization's growing AI initiatives. The successful candidate will help ensure data assets are discoverable, reliable, well-documented, and aligned with business needs while contributing to broader data literacy and AI readiness goals.

Key Responsibilities

Data & AI Enablement

• Partner with business stakeholders to identify opportunities for new data, analytics, and AI solutions.
• Help evaluate and prioritize use cases based on business impact and value.
• Act as a trusted resource for associates seeking data, reporting, or analytics support.
• Promote data literacy by helping users locate and leverage existing data assets and insights.
• Analyze requests and feedback to identify opportunities for process improvements and new analytics capabilities.

Documentation & Knowledge Management

• Create and maintain knowledge base articles and documentation related to data, analytics, and AI assets.
• Improve discoverability and usability of data assets through clear business-friendly documentation.
• Support ongoing efforts to enhance AI-powered support tools by ensuring accurate and well-maintained knowledge content.
• Contribute to data dictionaries, business definitions, metadata, and documentation standards.

Data Quality & Master Data Management

• Monitor business-critical datasets and data pipelines to ensure availability and quality.
• Collaborate with business and technical teams to improve the quality and consistency of master data, including customer, vendor, product, and pricing information.
• Escalate data quality issues and support remediation efforts with appropriate stakeholders.
• Assist with testing and validation of new data and analytics assets before release.

Metadata & AI Governance

• Maintain metadata, tagging structures, business definitions, and data classification standards.
• Support the preparation and curation of data for AI-enabled solutions, including Copilot, GenAI, and retrieval-based systems.
• Assist with data classification and governance initiatives to ensure sensitive information is properly managed.
• Help identify and mitigate risks related to AI outputs, including hallucinations, bias, and misinformation.
• Participate in continuous improvement efforts for AI-enabled tools and solutions.

Testing & Validation

• Perform functional testing, sanity checks, and data quality validation on reporting, analytics, and AI assets.
• Verify that delivered solutions meet intended business outcomes and user requirements.
• Support quality assurance activities across data and analytics initiatives.

Required Skills & Experience

• 1-3 years of experience in Business Intelligence, Reporting, Business Analysis, Data Management, or a related field.
• Strong communication skills with the ability to explain technical concepts to non-technical stakeholders.
• Excellent analytical and problem-solving abilities.
• Ability to distinguish between data issues, process issues, and business expectation gaps.
• Experience working collaboratively across business and technology teams.
• Strong organizational and time management skills in a fast-paced environment.
• Foundational understanding of data, analytics, reporting, and data governance concepts.

Preferred Qualifications

• Degree or diploma in Data Analytics, Business Analytics, Information Systems, Computer Science, Business Administration, or a related discipline.
• Familiarity with Microsoft data and analytics technologies, including Azure Data Lake, Databricks, and Microsoft Fabric.
• Experience with quality assurance, project coordination, or business analysis activities.
• Exposure to Dynamics 365 F&O data structures and entities.
• Understanding of metadata management, data governance, or AI-related initiatives is considered an asset.

What Success Looks Like

• Improved discoverability and usability of data assets across the organization.
• Increased adoption of analytics and AI capabilities by business users.
• Higher-quality master data and more reliable business reporting.
• Strong documentation and governance practices supporting data and AI initiatives.
• Effective collaboration between business stakeholders, Information Systems, and Data & Analytics teams.

Key things to look for:

• Business Analysis experience
• Data Analytics / BI background
• Experience gathering and documenting requirements
• Curiosity and enthusiasm around AI, Copilot, GenAI, or emerging technologies
• Ability to explain technical concepts to non-technical users
• Strong communication and documentation skills