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- Employment type
- Full-time
- Experience level
- Mid-level · 2+ years
- Minimum education
- Bachelor’s degree
- Posting language
- English
- Working hours
- 40 hours per week
- Seniority
- Mid-Senior level
Job summary
Clean, analyze, and validate operational data from multiple sources using Python, Excel, SQL, and Databricks, and support the maintenance of Power BI dashboards and reports. Identify trends and anomalies, connect data for root-cause analysis, and communicate actionable findings through reports and presentations to stakeholders and senior management.
Job details
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
What you’ll do
Clean, analyze, and validate operational data from multiple sources using Python, Excel, SQL, and Databricks, and support the maintenance of Power BI dashboards and reports. Identify trends and anomalies, connect data for root-cause analysis, and communicate actionable findings through reports and presentations to stakeholders and senior management.
Requirements
Requires 2–4 years of hands-on data analytics experience, a bachelor's degree in a related field, and experience analyzing operational data. Candidates should have strong Python and Excel skills, working knowledge of SQL, exposure to Power BI and Databricks, and the ability to communicate findings clearly to stakeholders.
Listed skills
- Power BI · Preferred
- SQL · Preferred
- Data Validation · Preferred
- Data analysis · Preferred
- Microsoft Excel · Preferred
- Root Cause Analysis · Preferred
- Python · Preferred
Other relevant skills
Identified from the job description. Confirm important requirements above.
- Python
- Pandas
- Excel
- Power BI
- SQL
- Databricks
- Data Cleaning
- Data Analysis
- Exploratory Data Analysis
- Dashboard Development
- Data Validation
- Operational Analytics
- Root-Cause Analysis
- PowerPoint Presentations
- Stakeholder Communication
Job areas
- Data & Analytics
- Technology
- Manufacturing
- Logistics