- What is Dimension Reduction? | Know the techniques
- Top Data Science Software Tools
- What is Data Scientist? | Know the skills required
- What is Data Scientist ? A Complete Overview
- Know the difference between R and Python
- What are the skills required for Data Science? | Know more about it
- What is Python Data Visualization ? : A Complete guide
- Data science and Business Analytics? : All you need to know [ OverView ]
- Supervised Learning Workflow and Algorithms | A Definitive Guide with Best Practices [ OverView ]
- Open Datasets for Machine Learning | A Complete Guide For Beginners with Best Practices
- What is Data Cleaning | The Ultimate Guide for Data Cleaning , Benefits [ OverView ]
- What is Data Normalization and Why it is Important | Expert’s Top Picks
- What does the Yield keyword do and How to use Yield in python ? [ OverView ]
- What is Dimensionality Reduction? : ( A Complete Guide with Best Practices )
- What You Need to Know About Inferential Statistics to Boost Your Career in Data Science | Expert’s Top Picks
- Most Effective Data Collection Methods | A Complete Beginners Guide | REAL-TIME Examples
- Most Popular Python Toolkit : Step-By-Step Process with REAL-TIME Examples
- Advantages of Python over Java in Data Science | Expert’s Top Picks [ OverView ]
- What Does a Data Analyst Do? : Everything You Need to Know | Expert’s Top Picks | Free Guide Tutorial
- How To Use Python Lambda Functions | A Complete Beginners Guide [ OverView ]
- Most Popular Data Science Tools | A Complete Beginners Guide | REAL-TIME Examples
- What is Seaborn in Python ? : A Complete Guide For Beginners & REAL-TIME Examples
- Stepwise Regression | Step-By-Step Process with REAL-TIME Examples
- Skewness vs Kurtosis : Comparision and Differences | Which Should You Learn?
- What is the Future scope of Data Science ? : Comprehensive Guide [ For Freshers and Experience ]
- Confusion Matrix in Python Sklearn | A Complete Beginners Guide | REAL-TIME Examples
- Polynomial Regression | All you need to know [ Job & Future ]
- What is a Web Crawler? : Expert’s Top Picks | Everything You Need to Know
- Pandas vs Numpy | What to learn and Why? : All you need to know
- What Is Data Wrangling? : Step-By-Step Process | Required Skills [ OverView ]
- What Does a Data Scientist Do? : Step-By-Step Process
- Data Analyst Salary in India [For Freshers and Experience]
- Elasticsearch vs Solr | Difference You Should Know
- Tools of R Programming | A Complete Guide with Best Practices
- How To Install Jenkins on Ubuntu | Free Guide Tutorial
- Skills Required to Become a Data Scientist | A Complete Guide with Best Practices
- Applications of Deep Learning in Daily Life : A Complete Guide with Best Practices
- Ridge and Lasso Regression (L1 and L2 regularization) Explained Using Python – Expert’s Top Picks
- Simple Linear Regression | Expert’s Top Picks
- Dispersion in Statistics – Comprehensive Guide
- Future Scope of Machine Learning | Everything You Need to Know
- What is Data Analysis ? Expert’s Top Picks
- Covariance vs Correlation | Difference You Should Know
- Highest Paying Jobs in India [ Job & Future ]
- What is Data Collection | Step-By-Step Process
- What Is Data Processing ? A Step-By-Step Guide
- Data Analyst Job Description ( A Complete Guide with Best Practices )
- What is Data ? All you need to know [ OverView ]
- What Is Cleaning Data ?
- What is Data Scrubbing?
- Data Science vs Data Analytics vs Machine Learning
- How to Use IF ELSE Statements in Python?
- What are the Analytical Skills Necessary for a Successful Career in Data Science?
- Python Career Opportunities
- Top Reasons To Learn Python
- Python Generators
- Advantages and Disadvantages of Python Programming Language
- Python vs R vs SAS
- What is Logistic Regression?
- Why Python Is Essential for Data Analysis and Data Science
- Data Mining Vs Statistics
- Role of Citizen Data Scientists in Today’s Business
- What is Normality Test in Minitab?
- Reasons You Should Learn R, Python, and Hadoop
- A Day in the Life of a Data Scientist
- Top Data Science Programming Languages
- Top Python Libraries For Data Science
- Machine Learning Vs Deep Learning
- Big Data vs Data Science
- Why Data Science Matters And How It Powers Business Value?
- Top Data Science Books for Beginners and Advanced Data Scientist
- Data Mining Vs. Machine Learning
- The Importance of Machine Learning for Data Scientists
- What is Data Science?
- Python Keywords
- What is Dimension Reduction? | Know the techniques
- Top Data Science Software Tools
- What is Data Scientist? | Know the skills required
- What is Data Scientist ? A Complete Overview
- Know the difference between R and Python
- What are the skills required for Data Science? | Know more about it
- What is Python Data Visualization ? : A Complete guide
- Data science and Business Analytics? : All you need to know [ OverView ]
- Supervised Learning Workflow and Algorithms | A Definitive Guide with Best Practices [ OverView ]
- Open Datasets for Machine Learning | A Complete Guide For Beginners with Best Practices
- What is Data Cleaning | The Ultimate Guide for Data Cleaning , Benefits [ OverView ]
- What is Data Normalization and Why it is Important | Expert’s Top Picks
- What does the Yield keyword do and How to use Yield in python ? [ OverView ]
- What is Dimensionality Reduction? : ( A Complete Guide with Best Practices )
- What You Need to Know About Inferential Statistics to Boost Your Career in Data Science | Expert’s Top Picks
- Most Effective Data Collection Methods | A Complete Beginners Guide | REAL-TIME Examples
- Most Popular Python Toolkit : Step-By-Step Process with REAL-TIME Examples
- Advantages of Python over Java in Data Science | Expert’s Top Picks [ OverView ]
- What Does a Data Analyst Do? : Everything You Need to Know | Expert’s Top Picks | Free Guide Tutorial
- How To Use Python Lambda Functions | A Complete Beginners Guide [ OverView ]
- Most Popular Data Science Tools | A Complete Beginners Guide | REAL-TIME Examples
- What is Seaborn in Python ? : A Complete Guide For Beginners & REAL-TIME Examples
- Stepwise Regression | Step-By-Step Process with REAL-TIME Examples
- Skewness vs Kurtosis : Comparision and Differences | Which Should You Learn?
- What is the Future scope of Data Science ? : Comprehensive Guide [ For Freshers and Experience ]
- Confusion Matrix in Python Sklearn | A Complete Beginners Guide | REAL-TIME Examples
- Polynomial Regression | All you need to know [ Job & Future ]
- What is a Web Crawler? : Expert’s Top Picks | Everything You Need to Know
- Pandas vs Numpy | What to learn and Why? : All you need to know
- What Is Data Wrangling? : Step-By-Step Process | Required Skills [ OverView ]
- What Does a Data Scientist Do? : Step-By-Step Process
- Data Analyst Salary in India [For Freshers and Experience]
- Elasticsearch vs Solr | Difference You Should Know
- Tools of R Programming | A Complete Guide with Best Practices
- How To Install Jenkins on Ubuntu | Free Guide Tutorial
- Skills Required to Become a Data Scientist | A Complete Guide with Best Practices
- Applications of Deep Learning in Daily Life : A Complete Guide with Best Practices
- Ridge and Lasso Regression (L1 and L2 regularization) Explained Using Python – Expert’s Top Picks
- Simple Linear Regression | Expert’s Top Picks
- Dispersion in Statistics – Comprehensive Guide
- Future Scope of Machine Learning | Everything You Need to Know
- What is Data Analysis ? Expert’s Top Picks
- Covariance vs Correlation | Difference You Should Know
- Highest Paying Jobs in India [ Job & Future ]
- What is Data Collection | Step-By-Step Process
- What Is Data Processing ? A Step-By-Step Guide
- Data Analyst Job Description ( A Complete Guide with Best Practices )
- What is Data ? All you need to know [ OverView ]
- What Is Cleaning Data ?
- What is Data Scrubbing?
- Data Science vs Data Analytics vs Machine Learning
- How to Use IF ELSE Statements in Python?
- What are the Analytical Skills Necessary for a Successful Career in Data Science?
- Python Career Opportunities
- Top Reasons To Learn Python
- Python Generators
- Advantages and Disadvantages of Python Programming Language
- Python vs R vs SAS
- What is Logistic Regression?
- Why Python Is Essential for Data Analysis and Data Science
- Data Mining Vs Statistics
- Role of Citizen Data Scientists in Today’s Business
- What is Normality Test in Minitab?
- Reasons You Should Learn R, Python, and Hadoop
- A Day in the Life of a Data Scientist
- Top Data Science Programming Languages
- Top Python Libraries For Data Science
- Machine Learning Vs Deep Learning
- Big Data vs Data Science
- Why Data Science Matters And How It Powers Business Value?
- Top Data Science Books for Beginners and Advanced Data Scientist
- Data Mining Vs. Machine Learning
- The Importance of Machine Learning for Data Scientists
- What is Data Science?
- Python Keywords

Highest Paying Jobs in India [ Job & Future ]
Last updated on 27th Oct 2022, Artciles, Blog, Data Science
- In this article you will get
- 1.Introduction
- 2.List of the 10 highest-paying jobs in India
Introduction
This article talks about the top 10 jobs in India that pay the most money in a variety of fields, such as healthcare, IT, finance, etc., with no particular order. Check out the 10 best-paying jobs in India and how much they pay, according to job postings on PayScale.
List of the 10 highest-paying jobs in India
- Blockchain Developer
- Digital Marketing Managers
- Business Analyst
- Product Manager
- Full-stack Developer
- UI/UX Designer
- Cybersecurity Engineer
- Data Analyst
- Cloud Architect
- Data Scientist
Blockchain Developers:
The future of blockchain technology is bright. Blockchain development is one of the highest-paying jobs available today, not just in India but also in other parts of the world and in different industries. Blockchain technology is combined with machine learning and artificial intelligence. Blockchain is used by organizations to record data and store it in a ledger. Blockchain developers are experts at building and implementing solutions and architectures with the help of blockchain methodologies.
Qualification:
When hiring blockchain developers, recruiters look for certain skills and qualifications, like a BE or B. Tech degree in IT, skills in programming languages like C, C++, C#, Java, JavaScript, and Python, knowledge of Bitcoin Blockchain, Ethereum, etc., and so on.
Salary:
Blockchain experts in India earn an average of 803,004 per year. This can go up to 2,000,000 per year with the right skills and experience.
The Top Companies Hiring Blockchain Developers:
- Here are a few of the best companies that are hiring after you become a Blockchain Developer.
- Accenture, Tata Consultancy Services, Tech Mahindra, and Blockchain App Factory.
Digital Marketing Managers:
Digital Marketing:
Digital marketing has become a key part of all businesses, whether they are large MNCs or small businesses and startups. With the rise of digitization and improvements in IT, digital marketing is taking off and opening up new doors, which is why it has become one of the most sought-after career paths in India.
Qualification:
It will help you get into this field if you have a bachelor’s degree in marketing, but it is not required. You could also have a degree in economics, law, etc.
Salary:
In India, digital marketing managers make an average of 600,000 per year. Depending on the subfield and their skills, this can go up to 2,000,000 per year.
Top Companies Looking for Digital Marketing Managers:
- Amazon.com Red Ventures

Business Analyst:
A business analyst is one of the best-paid jobs not just in India, but all over the world. The jobs of a business analyst range from business architect, business systems analyst, and enterprise analyst to product owner and product manager.
As part of their roles and responsibilities, business analysts have to do real-time analysis to help make decisions and to help make decisions. A business analyst in any company is known to work with the company’s top management to make decisions based on data.
Aside from this, business analysts are also responsible for finding ways to improve different processes, solving business problems through technical solutions, documenting technical and functional designs, and improving operational effectiveness.
Qualification:
For a career as a business analyst, you must have a bachelor’s degree. Aside from this main requirement, your job will be easier if you know the basics of programming and have knowledge of and experience with writing SQL queries. Strong communication and negotiating skills would be a big plus. Also, you can take a Business Analyst course from a well-known institute and get certified in this technology.
Salary:
The average salary of a business analyst in India is 800,000 p.a., which can go up to 17,00,000 p.a. with experience.
Top Companies Looking for Business Analysts:
- American Express’s Accenture
- Deloitte Tata Consultant Services
- The Cognizant Technology Solutions
Product Manager:
A product manager is an important part of any IT organization, but they are not the same as a project manager. A product manager decides on the strategies that need to be used and works with the rest of the team to make sure that the required product is made.
A product manager is in charge of assigning projects and deciding who works on what. They are also in charge of helping team members with the project and talking about the product’s scope and milestones while it is being made.
A product manager is responsible for delivering plans to reach the estimated tactical and strategic goals, managing and implementing marketing processes, and making a portfolio of the products. It is also one of the best paying jobs in commerce.
Qualification:
A product manager needs a bachelor’s degree in business administration, economics, management, or any other related field.
Salary:
The average salary of a product manager in India is 1,686,467 per year, and this can go up to 3,000,000 per year.
The Top Companies Hiring for Product Managers:
- Uber
- Amazon
- Microsoft
Full-Stack Developer:
A full-stack developer is someone who works on building and maintaining a website for an organisation. Full-stack developers are very important to an organization’s IT field because they work on both the frontend and backend of applications. They are also responsible for fixing problems on the website’s front end and back end. It is one of the highest-paying computer science jobs in India.
Qualification:
For you to become a Full Stack Developer, you must have a bachelor’s degree, preferably in IT. Also, you must have excellent coding skills and be fluent in both frontend and backend languages, such as HTML, CSS, Java, JavaScript, Python, C, Ruby, etc. You’ll also need to know the basics of SQL and other databases.
Salary:
The average salary of a full stack developer in India is 596,650 per year. This amount can go up to 1,000,000 with experience.
Top Companies Hiring Full Stack Developers:
- Accenture
- IBM
- Tata Consultancy Services
- SAP
- Cognizant Technology Solutions, etc.
UI/UX Designer:
A UI or UX designer has to think about many things when making a product, like how it looks, how easy it is to use, how it works, how it will be branded, and how it will be marketed. Their work is mainly about how a user interacts with a product from start to finish. The work also includes finding new opportunities for the product and business.
Given how many things they do, it’s no surprise that UI/UX designers are one of the most sought-after professionals in product design. A lot of companies hire UI/UX designers, and product-based companies pay UI/UX designers very well.
Qualification:
UI/UX designer stands for user interface and user experience designer. The main goal of a UI/UX designer is to build a product that is easy to use and gives a good user experience. In a company that focuses on making products, a UI/UX designer makes a lot of money.
Salary:
Starting UI/UX designer salaries in India can be anywhere from 20,000 to 25,000 per month. With up to two years of experience, the salary goes up, and the average salary per year comes to around 700,000.
Top companies hiring for this job:
Microsoft, Google, Accenture, Cognizant Technology Solutions Cybersecurity Engineer
Most, if not all, companies today have a strong presence on the internet. This makes protecting and securing their data and assets even more important and difficult.
Cybersecurity Engineer:
Cybersecurity is not just a requirement, but a must for all companies with data online. Because of this, the demand for cybersecurity engineers is growing, making it one of the highest-paying tech jobs in the world.
They need to make sure that no one else can access their data. They make sure that the users have only the access they need and nothing more, and so on. They are among the most important workers in a company.
It is one of the best jobs in India because companies will always need these professionals, so there will always be job openings for them.
Qualification:
When applying for a job in cybersecurity, you must have a degree in computer science, statistics, mathematics, or a similar field. Also, you need a certification in a certain area, depending on the job you want.
Companies Hiring Cybersecurity Engineers:
- AppleM
- New York’s Federal ReserveM
- General MotorsM
- IntelM
- Boeing Data AnalystM

Data Analyst:
A data analyst gathers, cleans, and analyses data sets to find answers to questions or solve problems. Using tools for data analysis, a data analyst looks at information closely and comes up with meaningful insights. Meaningful data pulled from a huge pile of data helps employers or clients make important decisions by pointing out facts and trends.
A data analyst’s typical tasks include using advanced computer models to get the data, doing a final analysis to provide additional data screening, preparing the data based on the analysis, and presenting it to the higher management.
Qualification:
For an entry-level data analyst job, you should have a degree in mathematics, statistics, or economics. Aside from this, having a good understanding of programming languages like R, Python, C++, Java, MATLAB, and PHP is very helpful because it will make the data extraction process easier.
Salary:
The average annual salary for a data analyst is 600,000, but you can make up to 1,000,000 p.a. depending on how much experience you have.
Cloud Architect:
A cloud architect knows everything there is to know about cloud computing, including its roles and how it is used in the market. Cloud architects are in high demand in the IT industry because all companies use the cloud and need them for maintenance and purchasing.
Cloud architects work in the IT field and lead a team that comes up with plans for building and deploying applications. One of their main jobs is to watch what’s happening in the cloud and design and move applications. The work of cloud architects in companies is very important, and they report directly to senior management, like the chief technical officer, CEO, director, etc.
Qualification:
To become a cloud architect, you need to have experience in IT. Knowing programming languages like Python, Ruby, and Elixir can be very helpful.
Also, people with strong leadership skills and good written and spoken communication skills are in high demand for the job. It’s also good to be good at designing and setting up cloud infrastructure.
Top Cloud Architects-Hiring Companies:
- Hewlett-Packard
- EMC
- IBM
- Microsoft
- Amazon Data Scientist
Data Scientist:
A data scientist is basically a “Big Data wrangler” who collects and analyzes large, unstructured data sets. They use a variety of mathematical and analytical skills to find meaningful data that can be used to make decisions.
To be a good data scientist, you must be able to find and manage data trends, which requires analytical skills in both technology and social science.
Data scientists use a variety of skills, depending on what industry they work in and what their job responsibilities are, to turn pieces of data into meaningful insights. Most data scientists are familiar with programming languages like R and Python. Data scientists also have to clean data, do research, manage warehouses and structures.
Qualification:
Usually, a bachelor’s degree in computer science is preferred for a data scientist. Even though it’s not required, some employers also look at academic credentials to see how a candidate would handle a data science job.
Salary
ndia has the second-highest demand for data scientists, with about 50,000 job openings. An entry-level data scientist with one to four years of experience makes an average of 610,811 per year. After a few years, a Data Scientist makes around 1,000,000 per year.
Top Companies Seeking Data Scientists:
- Amazon
- Oracle
Here are the top 10 highest-paying jobs in India in 2022. This will help you understand the salary ranges available in different job sectors. So, check out these options and choose the career that’s best for you.