Junior Data Analyst

Key Responsibilities

• Extract, clean, and transform data from multiple sources using

  SQL and Python (pandas)

  .
• Write efficient SQL queries using

  DDL, DML, DCL, and TCL commands

  .
• Apply

  filtering, grouping, and aggregation

  (WHERE, GROUP BY, HAVING) for data analysis.
• Perform different types of

  joins

  (INNER, LEFT, RIGHT, FULL, CROSS) to combine datasets.
• Create and maintain

  CTEs, subqueries, and views

  for modular query design.
• Use

  window functions

  for analytical operations like ranking and cumulative totals.
• Implement

  constraints

  and maintain data integrity across tables.
• Develop

  stored procedures

  for automating data extraction and reporting tasks.
• Utilize

  Python (pandas, numpy)

  for data manipulation and ETL (Extract, Transform, Load) workflows.
• Create visualizations using

  matplotlib, seaborn, or plotly

  to present data insights.
• Collaborate with business stakeholders to understand requirements and deliver accurate, meaningful reports.
• Support the creation of

  interactive dashboards

  in

  Power BI

  or

  Tableau

  .

Key Skills & Technical Proficiency

SQL & Database Skills

Strong understanding of SQL fundamentals (DDL, DML, DCL, TCL).

Hands-on experience with joins, subqueries, and CTEs.

Familiar with window functions, views, and stored procedures.

Basic knowledge of data modeling and constraints (Primary Key, Foreign Key, etc.).

Python for Data Analysis

Proficiency in Python programming for data processing and automation.
Hands-on with pandas and numpy for data cleaning, wrangling, and transformation. Basic understanding of ETL concepts and using Python for data extraction from APIs, CSVs, or databases. Familiarity with data visualization libraries: matplotlib, seaborn, or plotly.

Analytical & Reporting Tools

Proficiency in Excel / Google Sheets for data cleaning and basic analysis.

Exposure to Power BI, Tableau, or similar visualization tools (preferred).

Understanding of basic ETL concepts and data pipelines (nice to have).

Soft Skills

Strong attention to detail and logical thinking.

Good communication and presentation skills.

Ability to work with cross-functional teams and deliver within deadlines.

Willingness to learn and grow in the analytics domain.