Analyste de données principal modernisant les plateformes et pipelines de données d’EDC, société financière publique canadienne. Traduction des besoins opérationnels en modèles, règles de transformation et récits utilisateurs.
About the role
- Senior Data Analyst utilizing BigQuery and SQL Server to analyze transportation data for Ford. Leading investigations and collaborating across teams to support data-driven decision making.
Responsibilities
- Lead timely analysis for evolving, high-priority stakeholder questions; clarify problem statements, align on definitions, and deliver accurate findings with supporting evidence
- Analyze time-ordered event/telemetry data at scale to establish context around key outcomes, identify precursor signals, and measure the frequency of specific event sequences
- Write efficient, well-structured SQL for analytical workflows, including heavy use of window functions for sequencing, sessionization, and 'leading up to' / 'following' event context
- Analyze non-time-series operational datasets in SQL Server; join across tables, validate definitions, and reconcile findings with event-based analytics where applicable
- Assess data quality and result validity, identify anomalies, form and test hypotheses, and iterate analyses as new information emerges
- Integrate and reason across multiple data sources to provide a coherent view of what happened and under what conditions
- Work with stakeholders to define detection requirements, author and refine rule logic for our log-pattern analysis tool, execute investigations, and summarize findings along with recommended rule improvements
- Deliver outputs ranging from concise executive summaries to detailed technical write-ups that document methods, assumptions, and contributing factors
- Work closely with engineering, product, and process-improvement stakeholders (including Six Sigma/Black Belt practitioners) to frame questions, define metrics, and support structured root-cause analysis efforts
- Communicate complex findings calmly and clearly in high-visibility settings; distinguish evidence from hypotheses and avoid premature conclusions
Requirements
- Bachelor’s degree in Data Science, Computer Science, Statistics, Engineering, or a related quantitative field
- Minimum 3 years experience in data analysis, including time-series/event correlation and relational (non-time-series) analysis
- SQL, including expert use of analytical/window functions with BigQuery and SQL Server (or equivalent relational database) experience
- Writing performance-conscious queries over large datasets (e.g., partitioning/clustering-aware approaches, minimizing unnecessary scans, and validating results efficiently)
- Minimum 5 years of experience in visualization/reporting tools such as Power BI or Looker Studio
- Familiarity with structured problem-solving/continuous improvement approaches (e.g., Six Sigma, DMAIC) and comfort collaborating with Black Belt–level stakeholders
Benefits
- successful candidates will be required to provide proof of degree completion for the highest level of education attained
- if the degree was obtained from a school outside of Canada, an Education Credential Assessment report showing Canadian equivalency is also required
- identification of anomalies, validation of assumptions, and use of data to test hypotheses and refine problem statements
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