Data Analyst

Job Summary

Technical Skill Matrix Category Requirements: Must-Have (Min. 4 required): SQL (Joins, Aggregations, Subqueries), Python (Pandas, NumPy) or R, Advanced Excel (Pivot Tables, VLOOKUP/XLOOKUP), Power BI or Tableau, Data Cleaning & Preprocessing, Basic Statistics & EDA, Git & GitHub. Good to Have : PostgreSQL / MySQL optimization, Data Warehouse basics (BigQuery/Snowflake), Automated reporting scripts, Scikit-learn, Cloud services (AWS S3/RDS). Database & Analytics: Complex SQL queries, ETL process support, Exploratory Data Analysis (EDA), Relational database modeling. Tools & Platforms : SQL Server, MySQL, Power BI, Tableau, Jupyter Notebooks, Git, Excel

Responsibilities

• Extract, clean, transform, and validate structured and unstructured data from multiple database sources.
• Write efficient SQL queries and Python scripts to perform exploratory data analysis and ad-hoc analytics.
• Design, build, and maintain automated interactive dashboards and key performance metric reports using Power BI/Tableau.
• Identify operational trends, anomalies, and correlations to support business decision-making.
• Assist team leads in designing scalable data pipelines and maintaining data hygiene standards.
• Present complex data findings into actionable insights through visual charts and clear documentation.

Requirements

Must-have

• SQL (Joins, Aggregations, Subqueries)
• Python (Pandas, NumPy) or R
• Advanced Excel (Pivot Tables, VLOOKUP/XLOOKUP)
• Power BI or Tableau
• Data Cleaning & Preprocessing
• Basic Statistics & EDA
• Git & GitHub

Good to have

• PostgreSQL / MySQL optimization
• Data Warehouse basics (BigQuery/Snowflake)
• Automated reporting scripts
• Scikit-learn
• Cloud services (AWS S3/RDS)

Tools & Platforms

• SQL Server
• MySQL
• Power BI
• Tableau
• Jupyter Notebooks
• Git
• Excel

Preferred Skills

• Strong knowledge of writing Python automation scripts for routine data extraction and reporting
• Experience integrating business intelligence tools with live SQL databases or web APIs
• Basic understanding of predictive modeling techniques and data warehouse concepts

Keywords

Keywords: Data Analyst, SQL, Python, Pandas, Advanced Excel, Power BI, Tableau, Data Cleaning, Exploratory Data Analysis, MySQL, Dashboards, Data Visualization, Statistics, ETL.

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