Data Analyst

Job Title: Data Analyst
Department: Data Analytics / Business Intelligence
Experience: 0–3 Years
Employment Type: Full-time
Location: Depending on organization
Education: Bachelor’s degree in Computer Science, Statistics, Mathematics, Economics, Engineering, Business Analytics, or a related field.

Job Summary

A Data Analyst is responsible for collecting, cleaning, analyzing, and interpreting data to help an organization make better business decisions. The role involves working with large datasets, identifying trends and patterns, preparing reports and dashboards, and communicating meaningful insights to business teams.

The Data Analyst works closely with departments such as sales, marketing, finance, operations, HR, and management to understand their data requirements and provide accurate, actionable insights.

Key Responsibilities

• Collect data from databases, spreadsheets, APIs, and other sources.
• Clean and transform raw data to ensure accuracy and consistency.
• Analyze datasets to identify trends, patterns, relationships, and anomalies.
• Write SQL queries to retrieve and manipulate data from databases.
• Create reports, dashboards, and visualizations using tools such as Power BI, Tableau, or Excel.
• Prepare daily, weekly, monthly, and quarterly business reports.
• Monitor important business KPIs and performance indicators.
• Identify data quality issues and work with relevant teams to resolve them.
• Perform statistical analysis when required.
• Develop automated reports and dashboards to reduce manual work.
• Compare actual performance with targets and historical data.
• Support business teams with data-driven recommendations.
• Communicate analytical findings to technical and non-technical stakeholders.
• Maintain documentation for datasets, reports, dashboards, and analytical processes.
• Ensure data confidentiality and follow organizational data-security policies.

Required Technical Skills

1. SQL

• Strong knowledge of SQL fundamentals.
• SELECT, WHERE, GROUP BY, ORDER BY.
• JOINs.
• Subqueries.
• Aggregate functions.
• CASE statements.
• Common Table Expressions (CTEs).
• Window functions.
• Data filtering and transformation.

2. Microsoft Excel

• Formulas and functions.
• VLOOKUP/XLOOKUP.
• INDEX and MATCH.
• Pivot Tables.
• Charts and graphs.
• Conditional formatting.
• Data cleaning.
• Basic Excel automation/macros can be an advantage.

3. Data Visualization

Knowledge of one or more:

• Power BI
• Tableau
• Looker Studio
• Excel dashboards

Ability to create:

• KPI dashboards
• Bar charts
• Line charts
• Pie/donut charts
• Tables
• Interactive reports
• Performance dashboards

4. Programming

Knowledge of Python is commonly preferred.

Important libraries include:

• Pandas
• NumPy
• Matplotlib
• Seaborn
• Scikit-learn — useful for basic predictive analytics

Analytical Skills

A Data Analyst should be able to:

• Understand business problems.
• Convert business requirements into analytical questions.
• Identify relevant data sources.
• Detect trends and patterns.
• Perform root-cause analysis.
• Interpret statistical information.
• Identify outliers and inconsistencies.
• Generate meaningful business insights.
• Make data-driven recommendations.
• Explain complex data in a simple manner.

Soft Skills

• Strong problem-solving skills.
• Good communication skills.
• Attention to detail.
• Logical and analytical thinking.
• Time-management skills.
• Ability to work independently and in teams.
• Good presentation skills.
• Ability to communicate with non-technical stakeholders.
• Willingness to learn new tools and technologies.

Typical Day-to-Day Activities

A Data Analyst may start the day by reviewing business requests or KPI reports. They may then extract data using SQL, clean the data using Excel or Python, analyze the results, and update a Power BI or Tableau dashboard.

They may also attend meetings with business teams to understand problems such as:

• Why did sales decrease this month?
• Which products are performing best?
• Which customers are likely to leave?
• Which region has the highest revenue?
• Why are operational costs increasing?
• Which marketing campaign generated the most leads?

The analyst then uses available data to answer these questions and presents the findings to stakeholders.

Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Statistics, Mathematics, Engineering, Economics, Business Analytics, or a related discipline.
• Candidates with relevant certifications or practical projects may also be considered.
• Strong knowledge of SQL and Excel is highly desirable.
• Knowledge of Power BI/Tableau and Python is an advantage.

Experience

Freshers:
Candidates with strong knowledge of SQL, Excel, Power BI, and basic Python can apply for entry-level Data Analyst positions.

1–3 Years:
Candidates should have practical experience in data analysis, dashboard development, SQL querying, reporting, and communicating insights.

3+ Years:
Candidates may be expected to independently manage analytical projects, work with stakeholders, optimize reporting processes, and mentor junior analysts.

Preferred Certifications

• Microsoft Power BI Data Analyst certification
• Google Data Analytics Professional Certificate
• Tableau certifications
• SQL certifications
• Python/Data Analytics certifications