Data Analyst Salary

By | May 3, 2020
Data Analyst Salary

Data analysis is a meticulous and detailed job. Not only will this title help you grow technically and financially, but it will also give you exposure to different domains – you can be a data analyst in finance, education, telecom, sports, and many more fields. Even if your ultimate goal is to be a data scientist, it is good to start your career as a data analyst and then move up the ladder.

And about the salary – before we get into that, let us understand the term data analyst a bit more. For the impatient souls – the average salary can range from Rs. 8 lakhs to about Rs. 2,000,000 per annum. Regardless of the salary, you sure will have your place as the market is expected to grow by 28% or more for these jobs.


Career paths for Data Analyst

In this blog, we give you details on the most important roles and responsibilities within the scope of a data analyst and which of them can fetch you a fat package. Here is a quick snapshot from PayScale that indicates the possible career paths for a data analyst –

Pay scale

Source – Payscale

Why is big data so important?

So, what is all the buzz about? Why does everyone want to learn data science? If you already know the answers, you can as well move to the next section. However, here is a little background for the curious souls –

Almost everyone today has access to the internet and use different media platforms like YouTube, Gmail, LinkedIn, WhatsApp, Facebook, Netflix, Instagram, etc… From a user perspective, all these platforms are free. However, from a business point of view, this is where the real revenue comes from the gold mine – DATA! Some companies even pay you for submitting surveys that have simple questions you wouldn’t mind answering.

Have you ever thought…?

How come YouTube knows what kind of videos a user would like? How does Gmail put ads related to the conversations you have had on email?

All these and other media platforms continuously mine your data and get useful insights from it that helps them find new business use cases and do better marketing of their products and services.

It is interesting to know how much data is collected and evaluated on a daily basis. Think of a million users of Facebook, the average amount of browsing each user might do, number of links visited, pages liked and viewed, etc… – tells a lot about the user. Such data is collected by companies to promote their products and services to a target (certain group of) audience. If you are interested in travel and food, you will see more links related to that. If you are interested in higher education, you would get suggestions to like pages or join groups that you might find useful to pursue the same.

This huge amount of data is called as big data. Big data can be unstructured or structured.

How much data is created every day?

According to Forbes, 2.5 quintillion bytes of data are generated each day with the number increasing with the increase in the popularity of IoT. Google alone processes more than 40000 search requests per second – that is huge! Same way, Instagram gets close to 70000 million posts every minute.

It is not only humans that are creating and sharing data, data is created by the devices we use too. For example, smartwatches and sensors, smart TVs, mobile shopping etc… are some of the ways where data is not directly spelled out by us – it is predicted by the ‘smart’ system based on our activities.

What are the roles of a data analyst?

Typically, data analysts, process the big data and interpret the results for companies to use. They provide insights to solve business problems. Here are the main responsibilities of a data analyst –

  • Gather the necessary data and filter out the relevant information required to solve specific business problems.
  • Perform statistical analysis using different tools, surveys, and software programs on the chosen set of data
  • Process and interpret the data to form insights in the form of easy to understand charts and graphs, reports or presentations.
  • Present the interpretations and key information to the stakeholders and suggest various solutions to the problem, for them to make relevant business decisions

Data analysts,

  • deal with a lot of statistics and math to analyze data and present it in the form of trends and patterns,
  • have a good know-how of programming languages like Python, R to write scripts that can help you perform some repetitive tasks easily,
  • can write database queries to filter data from huge data sets easily and efficiently,
  • use excel spreadsheets to generate reports
  • are skilled at data management and manipulation
  • have good creative, problem-solving and analytical skills

You could be an architect, engineer, operations manager or an administrator and still go-ahead to be a data analyst. Even if you are not from a math background or have any programming experience, you can become a data analyst. There are plenty of free and paid courses available on the internet to learn statistics, linear regression, programming and SQL. You can also join a professional organization or talk to other data analysts via LinkedIn, GitHub, twitter etc… Choose one domain and focus on sharpening your skills specific to that domain.

But, why should you take the pain?

For one, the job is challenging and everyday new complex business problems arise – you will have loads of learning as you solve different types of problems.

Secondly, you will never be out of a job – until companies treat data as the king, your job is secure.

Last and most important, it is currently the highest paying job!

Data Analyst salary

The number of openings for data analysts increased manifold in 2019 and will further grow in 2020. As per IBM’s report, the combined annual demand of data engineers, data scientists, and data analysts will be about 7 lakhs in 2020.

The salary awarded to a data analyst varies based on different factors. Along with the base salary, a bonus component and profit-sharing are also awarded to data analysts. Here are some of the factors that determine the salary –

  • Level of experience
  • Type of industry
  • Roles and responsibilities – data mining, analytics, programming, data cleaning etc…
  • Location of work

For example, a fresher with training or certification might be getting lesser than a senior engineer with hands-on experience. The average salary of an entry-level data analyst is about 7lakhs.

Level of experience

Most of the available jobs are for candidates who have about 1-4 years of experience. This is followed by those having no or less than 1-year experience and then those who have about 5-9 years of experience. About 61% of the total data analyst jobs are for junior and medium level analysts who can work both on technological aspects as well as statistics.


Source – PayScale

Here is a quick table to show the pay scale based on the level of experience –

Title Role Salary (in India and US)
Entry-level Data Analyst Complete simple earning-based assignments, help senior data analysts to gather data, perform certain administrative tasks Rs. 4lakhs-9.36lakhs per annum


$34,466 per annum

Junior data analyst Use tools to gather and mine data, transform numbers to the plain English text, interpret data, clean data, implement strategies to improve efficiency Up to 16 lakhs per year


$70,000 per year

Senior data analyst (business data analyst) Train team members, handle a huge amount of data for high-profile or confidential projects, Interpret and analyze data, follow best practices and help in business process improvements More than 20 lakhs per annum


$106,600 per annum

Data analytics manager Supervise a team of data analysts, responsible for dealing with the company leaders, stakeholders and customers, provide business process recommendations, expedite the reporting process, ensure accuracy and efficiency of analyzing the data collected More than 20 lakhs per annum


$106,880 per annum

Type of Industry

TCS, Accenture, MuSigma, Amazon are companies that keep hiring more data analysts and the pay scale is good as well – about 5 lakhs per year for an entry-level data analyst. Myntra, an online shopping destination pays about 8 lakhs. Microsoft, Google, Apple, Facebook, Paypal, Twitter, Airbnb are some of the big players who pay a fat package – as the company size is bigger, the salary is huge too. Here is a graph indicating the type of industry and average salaries of data analysts in each industry –

Business Analysts are those who convert the data-driven insights and key information into business suggestions. They usually use Excel, SQL, and Tableau. At the entry-level, business analysts are paid anywhere from $55,000 to $70,000.

Financial analysts create financial models by analyzing micro and macroeconomic trends and predictions about the company’s performance based on financial data.

Healthcare data analysts use data for customer information, managing customer records, smoothen administration tasks and overall operations.

Market research analysts use sales, customer surveys and competitor research data to plan marketing strategies and optimize targeting and positioning efforts. They have to be creative in formulating new strategies and coming up with new stories and ideas. They mostly work with R/Python, SPSS (Statistical Package for the Social Sciences), SAS and Excel.

Transport data analyst determines gaps in the inefficiencies and budget variances and gives recommendations on improving the entire process of timeliness, types of good, cost and other factors. Amazon is currently the top employer of transportation analysts. They work with Excel, SQL and logistics management.

The salary ranges vary depending on the tools and amount of work involved. At entry-level, you may just have to gather the data from one source, however as you grow up the ladder, you may have to collect data from various sources within the industry – for example, competitors, surveys, research, past data and so on. Some industries pay more depending upon the amount of research and data interpretation involved.


US is currently the top payer for data analysts with average salary of $59,000, which again varies based on the city within US and other factors. In India, data analysts earn an average of Rs. 9,78,432 as the base amount on which bonus and other perks are added. Within India, the highest paying city in Gurugram, followed by Bengaluru and Pune.

If you have plans to relocate, the US, UK and Australia are 3 other good options to choose where base pays are in the range of USD 92,164, GBP 55,550 and AUD 119,000 respectively.

Roles and responsibilities

Based on your experience, you might be given tasks – for example, as an entry-level data analyst, you will be given the task to collect and filter the data or clean the data. As you reach up the career ladder, you might be able to do more complex tasks like deriving business interpretations from the data and seeing the bigger picture. A data analyst’s salary also depends on the kind of roles he/she is performing. However, you can increase your chances of getting a good package by expanding your existing skillset. This will help you take up more challenging work in less time.

There are a lot of certifications and courses available on the internet. Other than the basic requirements for a data analyst, here are some tools that you can focus on –

  • Spark/Hadoop
  • Scala
  • D3
  • AWS/Azure
  • MapReduce
  • Apache Hive
  • PIG
  • Machine Learning
  • ETL

You can also take up freelancing projects from, Upwork, Fiverr and others to enhance your portfolio and gain more experience. This will help you get on-board in a company faster and with a better package.


Now that you know much about data analyst and the career prospects of this title, start working on your skills by taking up courses and certifications. Whether it is your first or second career, the data analyst is going to stay for decades and you will have to constantly update yourself with the industry needs. If you are a student, start with statistical analysis on your choice of domain. For example, the sports or entertainment industry could give you loads of data to work on. View your surroundings with a curious and creative mind and think about how you can work with numbers and interpret practical results.

Pick your domain, start learning through various tutorials and books and go for it!

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