Working alongside existing programs and technical staff, the Data Analyst provides focused analytical capacity during the model design and build phases. This includes validating and testing core data models, canonical definitions, and Unified Business Object designs using real environmental monitoring and regulatory data to ensure the data foundation reflects how the business operates.

Responsibilities
A. Model Validation
Test proposed canonical elements against actual datasets.
Validate Unified Business Object model assumptions using:
Historical monitoring data
Reporting templates
Program specific datasets
Surface edge cases early during design and build phases.
B. Semantic analysis at the core data layers
Analyze:
Measurement comparability
Unit normalization issues




Data type and temporal consistency (e.g., sample dates vs reporting dates)
Identify where:
Standardization is secure vs. standardization would break meaning
Produce evidence-based recommendations to support the data architecture.
C. Analytical Prototyping in the Data Management Platform
Build exploratory analytical views to test:
Aggregation behavior
Trend stability
Query feasibility at scale, especially for large, ambient monitoring datasets
Answer questions like:
Can this model support cross program trend analysis?
Does the chosen data model work at scale?
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📌 Data Analyst Hybrid Edmonton
🏢 Pathlion
📍 Edmonton