Data Analyst

On-site
Posted Oct 9, 2026
1 position

Opens LinkedIn

Employment type: Full-time
Experience level: Entry, Junior · 0+ years
Posting language: English
Working hours: 40 hours per week
Seniority: Entry level
Application method: Direct apply is available

Job summary

Collect, clean, validate, and analyze data from multiple sources, and create reports, dashboards, and visualizations to communicate insights. Analyze performance metrics, identify trends and anomalies, automate reporting workflows, maintain data quality, and present actionable recommendations to management.

Job details

Key Responsibilities Collect, clean, validate, and analyze data from multiple sources. Develop reports, dashboards, and data visualizations to communicate insights. Write and optimize SQL queries to extract and transform data. Analyze business and operational performance metrics. Identify trends, patterns, and anomalies in datasets. Translate business requirements into analytical solutions. Work with stakeholders to understand reporting and data requirements. Automate recurring reports and improve data-processing workflows. Maintain data accuracy, consistency, and quality. Present findings and actionable recommendations to management. Required Skills Strong knowledge of SQL. Advanced Excel skills, including PivotTables, XLOOKUP/VLOOKUP, formulas, and data analysis. Experience with Power BI, Tableau, or similar BI tools. Understanding of data cleaning, transformation, and visualization. Strong analytical and problem-solving skills. Good communication and presentation skills. Basic understanding of statistics and business metrics. Preferred Skills Python or R for data analysis. Experience with databases and data warehouses. Knowledge of ETL/data pipelines. Experience with cloud platforms such as AWS, Azure, or GCP. Familiarity with Power Query and DAX.

What you’ll do

Requirements

Requires strong SQL skills, advanced Excel proficiency, experience with a BI tool such as Power BI or Tableau, and knowledge of data cleaning, transformation, and visualization. Also requires analytical, problem-solving, communication, and presentation skills, with a basic understanding of statistics and business metrics; Python or R, databases, data warehouses, ETL pipelines, cloud platforms, Power Query, and DAX are preferred.