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hirly last saw it live on 15 September 2026. See similar open roles below, or browse all Data Analyst jobs.

SAIT

Senior Data Analyst

Calgary, AB

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hirly's read of this role

Seniority
Senior
Stated salary
$85,000 – $95,000 per year
Country
CA
Work mode
On-site / unstated
First seen by hirly
11 Sept 2026

Derived automatically from the posting.

the posting

Technology is just the start. At SAIT, our IT Services team collaborates across the institution to shape smarter, more connected ways of teaching, learning and working. We’re strategic thinkers, problem-solvers, and innovators who turn big ideas into digital solutions that move SAIT forward. Join us and help build what’s next.

The Opportunity

Job classification : P2041 - Systems Analyst II

Salary range: $85,000 - $95,000

Placement within the range is typically based upon a review of skills, experience, and internal equity.

Hours per week: 37.5

Paid leave: 4 Weeks Vacation / 14 Flex Days per year

Deadline to apply: 4:00 PM, September 15, 2026

The Senior Data Analyst is a senior technical contributor within SAIT’s Data Governance Office, responsible for leading assigned data quality, data management, analytics, and governance implementation activities across the institution.

Reporting to the Supervisor, Data Management , the Senior Data Analyst is responsible for the assessment, improvement, and monitoring of institutional data quality. The position ensures trusted, well-governed data is available to support decision-making, operational excellence, compliance, and institutional objectives.

This role combines data governance, analysis, and data quality responsibilities to ensure the accuracy, consistency, and integrity of institutional data. Responsibilities include handling data profiling, complex data quality investigations, remediation initiatives, stewardship activities, metadata management, and governance process improvements.

The role facilitates collaboration with data stewards, trustees, business stakeholders, data engineers, and technical teams to resolve data quality issues, gain alignment on business rules and data standards, promote data literacy, and ensure compliance with institutional data policies and standards.

Original posting on SAIT's site ↗

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