Data Analyst

Position overview

Data analysis and insights

• Query and interpret HMIS, data warehouse, and other relevant data for CHF and system-planning priorities.
• Analyze homelessness, service use, housing outcomes, and system performance, including inflows, outflows, placements, and returns to homelessness.
• Investigate changes, anomalies, and emerging issues; conduct cohort and comparative analyses and apply appropriate statistical methods.

BI, reporting, and decision support

• Develop, enhance, and maintain dashboards and analytical products; turn user needs into measures, reports, and visualizations.
• Produce recurring and ad hoc analysis for CHF leadership, System Planning, government, funded agencies, and other stakeholders.
• Explain findings, assumptions, and limitations to technical and non-technical audiences and provide context for decision-makers.

Data quality and collaboration

• Validate outputs, investigate unexpected or incomplete results, and apply consistent definitions, business rules, and calculation methods.
• Identify data-quality issues, reconcile results across datasets, and document limitations affecting interpretation.
• Collaborate with CHF teams and partners, automate repeatable work, and improve reporting practices and analytical products.

Education and experience

• Graduate degree in Statistics, Data Science, Computer Science, Economics, Mathematics, quantitative social science, or another analytically focused discipline; equivalent education and relevant experience may be considered.
• 2–4+ years in data analysis, BI, reporting, or a related analytical role, with experience handling complex datasets and communicating findings.
• Experience developing dashboards, reports, and visualizations for operational or decision-making audiences.

Technical capabilities

• Strong SQL, including querying, joining, aggregating, and validating relational data.
• Experience with BI and visualization tools such as Power BI, Qlik Sense, or Tableau; these are listed as examples.
• Strong analytical and quantitative reasoning, descriptive statistics, data validation, reconciliation, and data visualization skills.
• Python or R, Azure, Databricks, or other cloud-based data environments are assets.

Additional relevant experience

• Experience with administrative, health, social-service, government, or other complex real-world data is an asset.
• Homelessness, housing, or social-sector experience is an asset but is not required.
• The role calls for clear communication, collaboration, initiative, organization, and sound judgment about data quality and context.

About Calgary Homeless Foundation