City Of Article

The Indian data analytics market is expected to witness significant growth through 2030 as businesses increasingly invest in Artificial Intelligence (AI), Business Intelligence (BI), and data-driven decision-making. As a result, the demand for skilled Data Analysts is rising rapidly across India's IT, banking, fintech, e-commerce, healthcare, and consulting sectors. 

From leading employers such as TCS, Infosys, Wipro, Accenture, Deloitte, PhonePe, Flipkart, Razorpay, and analytics-focused companies like Fractal Analytics and Tiger Analytics to global technology companies with large operations in India, organizations are actively hiring Data Analysts who can transform raw data into actionable business insights.

But which companies are hiring the most Data Analysts in India in 2026? What skills are recruiters looking for? And how can freshers prepare for these opportunities?

In this guide, you'll discover the top companies hiring Data Analysts in India, the skills they expect, salary trends, and the career roadmap needed to succeed in the analytics industry.

Key Takeaways From This Article

? Top companies hiring Data Analysts in India in 2026

? Industries creating the highest demand for analytics professionals

? Average Data Analyst salaries for freshers and experienced candidates

? Essential skills recruiters look for, including SQL, Power BI, Python, and Generative AI

? Why AI is creating new opportunities for Data Analysts rather than replacing them

? Practical steps to prepare for Data Analyst interviews and job opportunities

? A complete roadmap to build a successful career in Data Analytics

Whether you're a student, recent graduate, or working professional exploring analytics careers, this guide will help you understand the current job market and the skills needed to stand out in 2026.

Why Data Analysts Are in High Demand in 2026

The Rise of Data-Driven Businesses

Every business today generates enormous amounts of data through websites, mobile apps, transactions, social media platforms, customer interactions, and operational systems. Organizations need professionals who can transform this raw information into actionable insights. Data Analysts help companies answer important questions such as:

• What products are performing best?


• Which marketing campaigns deliver the highest ROI?


• Why are customers leaving?


• How can operational costs be reduced?


• What trends can help predict future growth?

As businesses become increasingly data-driven, the need for analytics professionals continues to expand.

Why Do Companies Need Human Analysts?

Despite advancements in AI, businesses still require professionals who can:

• Understand business objectives


• Interpret analytical results


• Identify data quality issues


• Communicate findings to stakeholders


• Make recommendations based on insights

Human judgment, critical thinking, and business understanding remain essential in analytics roles.

Industries Creating the Most Analytics Jobs

Some of the fastest-growing sectors for Data Analysts include:

• Information Technology


• Banking and Financial Services


• E-Commerce


• Healthcare


• Retail


• Telecommunications


• Consulting


• Logistics and Supply Chain


• Manufacturing

Top Companies Hiring Data Analysts in India in 2026

1. Google India 

Google's India operations continue to hire Data Analysts and Business Intelligence professionals across product, cloud, advertising, and customer analytics teams.

Skills Google Looks For

• SQL


• Python


• Statistics


• Data Visualization


• Problem Solving

Typical Responsibilities

• Analyzing product performance


• Building dashboards


• Conducting A/B testing


• Supporting business decisions with data

2. Amazon India 

Amazon India continues to hire Data Analysts to support e-commerce operations, logistics, customer experience, and business intelligence initiatives.

Skills Amazon Looks For

• Advanced SQL


• Excel


• Python


• Business Intelligence Tools


• Data Modeling

Typical Responsibilities

• Sales analysis


• Supply chain analytics


• Customer behavior analysis


• Operational reporting

3. Microsoft India 

Microsoft India offers opportunities for Data Analysts across cloud, enterprise technology, business intelligence, and product analytics functions.

Skills Microsoft Looks For

• SQL


• Power BI


• Azure Data Services


• Python


• Data Visualization

Typical Responsibilities

• Product analytics


• Cloud service performance analysis


• Business intelligence reporting


• Customer insights analysis

4. Tata Consultancy Services (TCS)

TCS continues to be one of India's largest employers of technology and analytics professionals. As organizations accelerate their digital transformation initiatives, TCS regularly hires Data Analysts to help clients leverage data for better business decisions.

Skills TCS Looks For

• SQL


• Power BI


• Excel


• Python


• Database Management

Typical Responsibilities

• Business reporting


• Data migration projects


• Analytics support


• Dashboard creation

5. Infosys

Infosys works with clients across industries such as banking, healthcare, retail, manufacturing, and telecommunications. The company actively recruits Data Analysts to support business intelligence, reporting, and digital transformation initiatives.

Skills Infosys Looks For

• SQL


• Power BI


• Python


• Data Visualization


• Analytical Thinking

Typical Responsibilities

• Data reporting


• Business analysis


• KPI tracking


• Customer analytics

6. Wipro

Wipro's analytics teams help organizations make data-driven decisions through reporting, visualization, and business intelligence solutions. The company offers opportunities for both freshers and experienced analytics professionals.

Skills Wipro Looks For

• SQL


• Excel


• Power BI


• Data Analysis


• Business Intelligence

Typical Responsibilities

• Data reporting


• KPI monitoring


• Dashboard creation


• Business performance analysis

7. HCLTech

HCLTech continues to expand its analytics and digital services portfolio as companies increasingly invest in data modernization and AI-driven solutions. Data Analysts play a key role in helping clients generate actionable business insights.

Skills HCLTech Looks For

• SQL


• Power BI


• Excel


• Python


• Data Visualization

Typical Responsibilities

• Business reporting


• Dashboard development


• Data analysis


• Performance tracking

8. IBM India

IBM India remains a major employer for analytics and AI professionals. The company leverages data analytics across cloud computing, enterprise solutions, automation, and artificial intelligence projects.

Skills IBM India Looks For

• SQL


• Python


• Data Visualization


• Business Intelligence


• Analytical Problem Solving

Typical Responsibilities

• Data analysis


• Reporting automation


• Business intelligence development


• Customer insights analysis

9. Fractal Analytics

Fractal Analytics is one of India's leading analytics and AI companies. It specializes in helping organizations use data, machine learning, and AI-driven insights to improve business outcomes.

Skills Fractal Analytics Looks For

• Python


• SQL


• Machine Learning Basics


• Data Visualization


• Statistical Analysis

Typical Responsibilities

• Predictive analytics


• Customer insights analysis


• AI-powered business solutions


• Data storytelling

10. Mu Sigma

Mu Sigma is widely recognized for helping global enterprises solve complex business challenges using analytics. The company remains a popular destination for aspiring Data Analysts looking to build strong analytical foundations.

Skills Mu Sigma Looks For

• Statistics


• SQL


• Excel


• Problem Solving


• Data Interpretation

Typical Responsibilities

• Business analytics


• Market research analysis


• Data-driven consulting


• Strategic decision support

11. Tiger Analytics

Tiger Analytics specializes in advanced analytics, business intelligence, and AI solutions. The company works with global clients across retail, healthcare, consumer goods, and financial services industries.

Skills Tiger Analytics Looks For

• SQL


• Python


• Power BI


• Data Visualization


• Analytical Thinking

Typical Responsibilities

• Business intelligence projects


• Customer behavior analysis


• Reporting and visualization


• Advanced analytics support

12. LatentView Analytics

LatentView Analytics helps organizations use data to improve business performance, customer experience, and operational efficiency. The company frequently hires Data Analysts for reporting, visualization, and analytics projects.

Skills LatentView Analytics Looks For

• SQL


• Excel


• Python


• Data Visualization


• Statistics

Typical Responsibilities

• Marketing analytics


• Customer analytics


• Revenue optimization analysis


• Dashboard reporting

13. PhonePe

As one of India's largest fintech companies, PhonePe relies heavily on analytics to improve customer experience, digital payments, fraud prevention, and business performance.

Skills PhonePe Looks For

• SQL


• Python


• Power BI


• Data Modeling


• Business Analysis

Typical Responsibilities

• Transaction analysis


• Customer behavior analytics


• Fraud monitoring


• Product performance tracking

14. Razorpay

Razorpay continues to expand its analytics capabilities to support digital payments, financial services, and business intelligence initiatives. The company offers exciting opportunities for data professionals interested in fintech.

Skills Razorpay Looks For

• SQL


• Python


• Excel


• Analytics Reporting


• Dashboard Development

Typical Responsibilities

• Payment analytics


• Customer insights


• Business reporting


• Product analytics

15. Flipkart

Flipkart uses data analytics extensively across e-commerce operations, inventory management, logistics, customer experience, and marketing optimization. The company continues to hire Data Analysts to support data-driven growth.

Skills Flipkart Looks For

• SQL


• Excel


• Power BI


• Python


• Data Interpretation

Typical Responsibilities

• E-commerce analytics


• Customer segmentation


• Inventory reporting


• Sales performance analysis

Quick Salary Comparison: Data Analyst Salaries in India (2026)

Salaries for Data Analysts in India vary based on location, industry, technical expertise, and experience level. Professionals skilled in SQL, Power BI, Python, and Generative AI often command higher salaries, especially in major technology hubs such as Bengaluru, Pune, Hyderabad, Mumbai, Chennai, and Gurgaon.

Top Cities Hiring Data Analysts in India

• Bengaluru


• Pune


• Hyderabad


• Mumbai


• Gurgaon


• Chennai


• Noida

Why India Is Becoming a Major Hub for Data Analytics Careers

India has become one of the fastest-growing markets for data analytics and AI-driven business solutions. With the rapid expansion of digital services, fintech platforms, e-commerce businesses, cloud technologies, and AI adoption, organizations are generating more data than ever before.

Cities such as Bengaluru, Pune, Hyderabad, Mumbai, Chennai, and Gurgaon have emerged as major hiring hubs for Data Analysts. Companies across industries are looking for professionals who can work with SQL, Power BI, Python, Excel, and Generative AI tools to support business growth and data-driven decision-making.

Which Industries Are Hiring the Most Data Analysts?

While technology companies are major employers, Data Analysts are now needed across nearly every industry.

1. IT and Software

Technology companies generate massive amounts of customer, operational, and product data. Analysts help organizations identify trends, optimize products, and improve user experiences.

2. Banking and Financial Services

Banks and financial institutions use analytics for:

• Risk assessment


• Fraud detection


• Customer segmentation


• Financial forecasting

3. E-Commerce

Online businesses depend heavily on analytics for:

• Customer behavior analysis


• Product recommendations


• Marketing optimization


• Inventory management

4. Healthcare

Healthcare organizations use data analytics to improve patient outcomes, optimize resources, and support decision-making.

5. Retail

Retail companies analyze purchasing patterns, customer preferences, and sales trends to improve profitability.

6. Consulting Firms

Consulting companies hire analysts to help clients solve business challenges using data-driven insights.

Top Skills Companies Look for in Data Analysts

Landing a Data Analyst job requires more than theoretical knowledge. Employers look for candidates who can work with real-world datasets and generate actionable insights.

1. SQL - SQL remains one of the most requested skills in Data Analyst job descriptions. Why it matters:

• Retrieve data from databases


• Perform data analysis


• Create reports


• Manage large datasets

2. Excel - Excel is still widely used across industries for:

• Reporting


• Data cleaning


• Pivot tables


• Business analysis
  
  
  

3. Power BI - Power BI helps analysts transform raw data into meaningful visual dashboards. Employers value professionals who can:

• Build dashboards


• Create reports


• Present business insights visually

4. Python - Python enables analysts to automate tasks and perform advanced analysis.Popular libraries include:

• Pandas


• NumPy


• Matplotlib


• Seaborn

5. Statistics and Data Visualization - Understanding data is not enough. Analysts must be able to explain findings clearly through visualizations and business reports.

6. Generative AI Tools - Increasingly, companies want analysts who understand:

• ChatGPT


• AI-assisted reporting


• Prompt Engineering


• Data storytelling using AI

This growing demand is one reason many learners are enrolling in a Data Analytics Course in Pune with Gen AI to stay competitive in the evolving job market.

Why Generative AI Skills Are Becoming Important for Data Analysts

Generative AI is changing how analysts work.

1. Using ChatGPT for Data Analysis -

Analysts can use AI tools to:

• Generate SQL queries


• Explain datasets


• Summarize reports


• Draft business insights

2. AI-Powered Reporting -

Instead of spending hours preparing reports, analysts can use AI tools to accelerate reporting and visualization workflows.

3. Automating Data Cleaning

AI can help identify inconsistencies, missing values, and anomalies in datasets, reducing manual effort.

4. Enhanced Data Storytelling

Generative AI can assist analysts in presenting complex insights in a way that business stakeholders can easily understand. At Fusion Software Institute, students learn industry-relevant tools such as SQL, Power BI, Python, Excel, and Generative AI applications through practical training and real-world projects.

How to Get Hired by Top Data Analytics Companies

1. Build Strong Technical Skills - Focus on mastering:

• SQL


• Excel


• Power BI


• Python


• Statistics

2. Work on Real-World Projects - Projects demonstrate practical abilities better than certifications alone. Examples include:

• Sales dashboards


• Customer analytics reports


• Financial analysis projects


• Business intelligence dashboards

3. Create a Strong Portfolio - Your portfolio should showcase:

Power BI dashboards

• SQL projects


• Python notebooks


• Business case studies

4. Earn Relevant Certifications - Certifications can validate your skills and improve credibility with employers.

5. Prepare for Interviews - Common interview topics include:

• SQL queries


• Excel functions


• Dashboard design


• Data cleaning techniques


• Business case studies

6. Develop Business Understanding - Top companies prefer analysts who understand both technology and business objectives.

Data Analyst Career Roadmap for Beginners

Step 1: Learn Excel - Build a foundation in spreadsheets, formulas, reporting, and data cleaning.

Step 2: Learn SQL - Understand how to query databases and analyze structured data.

Step 3: Master Power BI -  Learn dashboard creation, visualization techniques, and KPI reporting.

Step 4: Learn Python - Develop automation and advanced analytics skills.

Step 5: Understand Generative AI - Learn how AI tools can support analytics workflows and reporting.

Step 6: Build Projects - Apply your skills to real-world business problems.

Step 7: Apply for Entry-Level Roles