Data Analyst
Role Overview
Analyze structured operational data and produce insights, reports, and presentations.
Support the Data Analytics Lead; this is not a data architecture, data engineering, platform-design, or people-management role.
Key Skills for This Role
Full Job Posting
Role overview
Analyze structured operational data and produce insights, reports, and presentations.
Support the Data Analytics Lead; this is not a data architecture, data engineering, platform-design, or people-management role.
Responsibilities
- Clean, analyze, and derive insights from operational data using Python and Excel.
- Build and maintain Power BI dashboards and reports with the Data Analytics Lead; pull data from Databricks when required.
- Explore datasets for trends, patterns, and anomalies, and connect operational systems for root-cause analysis.
- Collect and validate stakeholder data and align definitions across sources.
- Present process-improvement initiatives and actionable findings to senior management and other stakeholders.
- Prepare accurate reports, charts, and summaries for review.
Required qualifications
- 2–4 years in a data analyst or similar hands-on analytics role.
- Bachelor’s degree in data science, engineering, computer science, supply chain, or a related field.
- Operational analytics exposure, such as production, quality, or supply-chain data.
- Strong Python and Excel skills; Power Query is a plus.
- Working SQL knowledge; exposure to Power BI, including dashboards and DAX basics, and Databricks.
- Comfort creating PowerPoint presentations, communicating with stakeholders, and working carefully with messy operational data.
Preferred experience
- Manufacturing, aerospace, or industrial operations exposure is a plus, but not required.
Pay and benefits
- Pay is $75,000–$80,000 per year.
- Benefits include casual dress, company pension, dental care, on-site parking, paid time off, RRSP match, vision care, and a wellness program.
Workplace
- Work location is in person.
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