Analyzes operational data using Python, Excel, SQL, Power BI, and Databricks to identify trends, anomalies, and process improvement opportunities. Builds and maintains dashboards, validates data across stakeholders and systems, performs root-cause analysis, and presents actionable findings to senior management. The role supports a lead analyst and focuses on hands-on analysis rather than architecture, engineering, or people management.
About the job
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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