C
Cyient
Data Analyst
Skills
SQL QueriesData EngineeringPythonData SciencepandasDatabricksData AnalysisProcess ImprovementSupply ChainPower BI
22 days ago
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Important information
Contract type:
Permanent
Location:
Montreal, QC, Canada
Work mode:
Onsite
Published on:
28 September 2026
What they need
Roles & Responsibilities
- Work with structured operational data using Python and Excel to clean, analyze, and compute insights
- Support the Data Analytics Lead in building and maintaining Power BI dashboards and reports
- Pull and work with data from Databricks when required for analysis
- Perform exploratory data analysis to identify trends, patterns, and anomalies in operational datasets
- Assist in connecting data across different operational systems to support root-cause analysis
- Collect data from different stakeholders, validate accuracy, and align on definitions across sources
- Create presentations summarizing process improvement initiatives for reporting to senior management
- Present insights and findings to different stakeholders, translating data into clear, actionable takeaways
- Prepare clear, accurate outputs (reports, charts, summaries) for review by the lead and stakeholders
Required
- 2-4 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
- Exposure to operational analytics -analyzing production, quality, supply chain, or similar operational data
- Strong Python skills for data manipulation and analysis (Pandas or similar)
- Strong Excel skills (formulas, pivot tables; Power Query is a plus)
- Working knowledge of SQL for querying and joining data
- Exposure to Power BI (building or maintaining dashboards, DAX basics)
- Exposure to Databricks -comfortable pulling and working with data hosted there
- Comfortable creating presentations (PowerPoint) to communicate findings to senior stakeholders
- Good communication skills -able to collect, validate, and align data with different stakeholders, and present insights clearly
- Good attention to detail and comfort working with messy, real-world operational data
- Manufacturing, aerospace, or industrial operations exposure is a plus, but not required
What This Role Is Not
- Not a data architecture, data engineering, or platform-design role
- Not a people-management role -you'll support the lead, not run the engagement independently
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