A data engineer is responsible for the construction and maintenance of an organization's data infrastructure. It includes ensuring that data is collected, stored, processed, and made available for use by other members of the organization. A data engineer may also be responsible for developing and maintaining data-related applications.
Data engineering has become one of the highly in-demand career options with lucrative pay packages. When it comes to data engineering, everyone is curious to know about the data engineer salary. However, before knowing the pay scale of data engineers, it is important to get an idea about their roles and responsibilities. Go for Big Data Certification online to build a robust skill set with the most powerful Big Data tools and technologies.
Who is a Data Engineer?
A data engineer is a professional who designs, builds, and engineers an infrastructure to transform data into formats helpful for data scientists. The architecture developed by data engineers helps the data scientists in storing, procuring, and using raw data for better analysis and interpretation. Engineers play an important role in converting vast volumes of data into understandable, valuable information for businesses.
Businesses usually deal with immense data so, processing, analyzing, and storing is often challenging. Meanwhile, the data engineers help in reducing the complexity of these processes by creating a reliable infrastructure. A data engineer creates pipelines for the effective extraction of vital data. The engineer also builds different algorithms for the consolidation and cleansing of data.
Data Engineer Average Salary Structure
In recent times, the demand for data engineers is quite high owing to the increasing need of businesses to analyze and organize huge data volumes. Even during the pandemic, the pay scale of the data engineers was good. On average, the big data engineer's salary in India is ₹836,443 annually. The senior data engineer's salary may be even more. However, the range can vary from ₹368k annually to ₹2 million annually.
A point to note here is that the data science engineer salary is dependent on several factors. The major factors include skills, experience, job role, company, and even location. Therefore, based on these factors, the salary of a data engineer will differ.
1. Data Engineer Salary: Based on Experience
The average annual big data engineer salary is $115,373. The salary range for data engineers varies depending on experience, location, and industry. A data engineer's salary is based on the candidate's years of working experience and skills. An average data center engineer's salary in India is ₹ 3.4 Lakhs per year, while an average analytics engineer's salary is ₹ 5.8 Lakhs per year. An azure data engineer's salary in India is ₹ 6.5 Lakhs annually.
Beginner
A data engineer is a professional responsible for designing, building, and maintaining data infrastructure. They are responsible for ensuring that data is accessible, reliable, and secure. A data engineer's salary is based on their experience and skills. A beginner data engineer can expect to earn an average annual salary of ₹3,30,000 per year.
Intermediate
In India, an intermediate data engineer with 4-9 years of experience can expect to earn an annual salary of ₹13,20,000. This figure is based on an analysis of data engineer salaries in India.
Advanced
The average salary for an advanced or senior data engineer with a working experience of 10-20 years is ₹21,40,00 per year.
2. Data Engineer Salary: Based on Location
India
In India, a data engineer typically earns an annual salary of around ₹10,77,477. This figure can vary depending on experience, skills, location, and industry. With a few years of experience, a data engineer in India can increase their salary, and those with more experience and expertise can earn a handsome salary. Data engineers in India can work in various industries, including IT, banking and finance, healthcare, manufacturing, and retail.
The location of a data engineer can also impact their salary. For example, those working in Mumbai or Bangalore can expect to earn more than those working in smaller cities. A data engineer in India can expect to earn a salary that is commensurate with their experience and skills. Those just starting their career can expect to earn a lower salary than those with more experience. However, with the right skills and experience, a data engineer in India can earn a good salary.
| Locations | Average Salary Annually (in INR) |
|---|
| Bengaluru | ₹931,331 |
| Mumbai | ₹729,561 |
| Pune | ₹861,549 |
| Gurgaon | ₹987,847 |
| Hyderabad | ₹980,530 |
| Kolkata | ₹524,000 |
| New Delhi | ₹902,317 |
| Ahmedabad | ₹450,000 |
| Chennai | ₹817,425 |
| Jaipur | ₹560,000 |
US
The average salary for a Data Engineer in the United States is $115,373 per year. However, the salary range of Data Engineers varies based on location and the company they are working in. There is a huge scope for career advancement for Data Engineers in the US, as there is a growing demand for skilled Data Engineers.
UK
The average salary for a Data Engineer in the United Kingdom is £61,125. However, salaries can vary significantly based on location. For example, a Data Engineer in London can expect to earn significantly more than one in a smaller city. Data Engineer salaries in the United Kingdom are influenced by many factors, including experience, education, skills, and demand. Generally, the more experience and expertise a Data Engineer has, the higher their salary will be.
Data Engineers with a master's degree or higher certifications can also expect to earn more than those without advanced degrees. The skills that are most in demand for Data Engineers tend to command the highest salaries. These skills include experience with big data platforms, such as Hadoop and Spark, as well as proficiency in programming languages, such as Java and Python. Demand for Data Engineers also plays a role in salary. Data Engineers who work in industries with high demand, such as finance and healthcare, can expect to earn more than those in less in-demand industries.
Australia
In Australia, the average salary for a data engineer is $131,668 per year. However, this number can vary depending on several factors, such as experience, skills, and location. Generally speaking, data engineers in Australia can expect to earn salaries that are above the average. This is due to the high demand for these professionals in the country, as well as the relatively high cost of living.
Canada
Data engineers in Canada earn an average salary of $101,530 per year. Salaries vary depending on experience, location, and employer. Data engineers who also possess software engineering skills are in high demand, and employers are willing to pay a higher salary for them. Data Engineer is a good career in Canada with overall good job satisfaction among employees.
Singapore
There is much variation in the salary of a data engineer based on their location. In Singapore, a data engineer can expect an average salary of $98,175 per year. Their experience and skills largely determine the salary of a data engineer in Singapore. Data engineers with more experience and better skills can expect to earn higher salaries. The most experienced and skilled data engineers in Singapore can expect to earn high salaries and extra benefits.
3. Data Engineer Salary Pay Scale Based on Skills
Skill is also one of the important determining factors of the salary packages of data engineers in India. The more skills the individual possesses, the higher the salary will be.
There are a number of skills that data engineers must acquire to enhance their earning potential. For instance, SQL is a valuable skill for data engineers compared to Microsoft Word.
Below is a list of the highly in-demand skills and the salary packages of the data engineers who possess those skills.
| Skills | Average Salary Annually (in INR) |
|---|
| SQL | ₹822,524 |
| Data Warehousing skills | ₹900,000 |
| Apache Spark | ₹966,687 |
| Programming Language (Python) | ₹802,380 |
| Hadoop | ₹872,216 |
| ETL (Extract, Transfer, Load) Skills | ₹872,886 |
Factors Affecting Data Engineer Salary
Let us explore the factors that affect data science engineer salary:
Location: Location is also a factor in determining a Data Engineer's salary. Developers who work in areas with a high cost of living tend to earn more than those who work in areas with a lower cost of living. This is because developers in high-cost areas can command higher salaries due to the increased demand for their skills.
Industry / Employer / Company: The industry a Data Engineer works in can have a significant impact on their salary. For example, developers who work in the finance industry tend to earn more than those who work in the retail industry. The company, a Data Engineer, works in can also affect their salary. Developers who work for large companies tend to earn more than those who work for small companies. The average salary of a data engineer in various companies is given below:
- Amazon: An Amazon data engineer's salary is ₹ 21,34,397 annually.
- Facebook: A Facebook data engineer's salary is ₹ 81,15,000 annually.
- Google: A Google data engineer's salary is ₹ 47,72,703 annually.
Experience: Experience is the most crucial factor in determining a Data Engineer's salary. Developers with more experience tend to command higher salaries than those with less experience. It is because experienced developers are more likely to be able to produce high-quality software that meets the needs of their employers.
Demand and Supply: The overall market conditions can affect the demand for developers. For example, during an economic downturn, companies may be less likely to hire new developers and likely to increase the salary of the developer, while when the demand is high, companies need more Data Engineers for their technology and are willing to offer a high salary to the developers. An increase in startups also leads to demand for Data Engineers.
Credentials / Certifications: Education also plays a role in determining a Data Engineer's salary. Developers with a bachelor's degree or higher tend to earn more than those without a college degree. This is because a college degree indicates that a developer has the necessary skills and knowledge to be successful in the field. One can check various courses online and get more certificates while having a full-time job.
Skills: Skills are also important in determining a Data Engineer's salary. Developers who are skilled in programming languages and software development tools tend to earn more than those who are not as skilled. This is because skilled developers are more likely to be able to create software that is of high quality and that meets the needs of their employers.
How to Improve Data Engineer Salary?
Skills
You can do a few key things to improve your data engineer salary. First, keep up with the latest trends in data engineering. New technologies and approaches are always being developed, so it is important to stay up-to-date. Second, get certified in popular data engineering tools and platforms. It will show employers that you have the skills they need. Finally, consider pursuing a master's degree in data engineering. It will give you the advanced skills and knowledge you need to stand out from the competition and also helps in increasing your salary.
Certifications
Investing in your education and professional development is another great way to improve your Data Engineer salary. Pursuing advanced degrees or professional certifications can show employers that you're committed to your craft and have the skills to back up your claims.
Degrees
One way is to get a degree from an accredited institution. It will ensure that your degree is recognized by employers and help you get a better-paying job. Getting more and more degrees will help you achieve your dream salary.
Experience
Another way to improve your salary is to get experience in the field. It can be done by working as a Data Engineer for a company or by working on your projects. The more experience you have, the more you will be able to negotiate for a higher salary.
Why are Data Engineers Paid So Much?
There are several reasons why data engineers are paid so much:
- The demand for data engineers is skyrocketing as more and more companies are looking to harness the power of data.
- Data engineers have a unique skill set that is in high demand. They can collect, process, and analyze large amounts of data quickly and efficiently.
- Data engineers are often able to work with a variety of different data sources, including structured and unstructured data. It allows them to provide insights that would otherwise be unavailable.
- Data engineers are often able to work with a variety of different technologies, which gives them a significant advantage over other types of engineers.
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Conclusion
A data engineer is a professional who is responsible for the collection, organization, and analysis of data. They work in various industries, including healthcare, finance, and manufacturing. Data engineers typically have a strong background in computer science and mathematics. Data engineers play a vital role in organizations that rely on data to make decisions.
They are responsible for ensuring that data is accurate, complete, and timely. They also work to improve the efficiency of data collection and analysis. Data engineers often work closely with data scientists. They may also collaborate with software engineers to develop new ways to collect and analyze data. Data engineering is a field that is expected to grow significantly in the next decade.
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