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Data Analyst

Cyient
Montréal, CAN
Full-time
Mid-Senior
Onsite
Discovered 3 weeks ago
Operational data analyticsPythonPandasExcelSQLPower BI

Full Job Posting

Roles and responsibilities

  • Clean and analyze structured operational data using Python and Excel; support Power BI dashboard and report development.
  • Pull data from Databricks as needed, perform exploratory analysis, and identify trends, patterns, and anomalies.
  • Connect operational-system data for root-cause analysis; collect, validate, and align data definitions with stakeholders.
  • Prepare presentations, reports, charts, and summaries; communicate process-improvement findings and actionable insights to stakeholders and senior management.

Required qualifications

  • Two to four years of experience 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 involving production, quality, supply chain, or similar operational data.
  • Strong Python skills for data manipulation and analysis; Pandas or similar is an example.
  • Strong Excel skills, including formulas and pivot tables; Power Query is a plus.
  • Working SQL knowledge for querying and joining data.
  • Power BI exposure, including dashboard building or maintenance and basic DAX, is listed as exposure.
  • Databricks exposure and comfort working with hosted data are listed as exposure.
  • Comfort with PowerPoint presentations, stakeholder communication, attention to detail, and messy real-world data.
  • Manufacturing, aerospace, or industrial operations exposure is a plus, but not required.

Role scope

The analyst supports the Data Analytics Lead and is not a data architecture, data engineering, or platform-design role.

The role is not a people-management position; the analyst supports the lead rather than independently running the engagement.

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