Data is omnipresent and is being created and processed by the second in almost every industry. This copious amount of data requires data scientists and engineers to interpret meaningful insights and drive business performance.
As per the Data Science Interview Report, data engineering was the fastest-growing position in the data science domain in 2020. Interviews for the job role increased by 40% in different industries, especially in FAANG companies. According to IDG Cloud Survey, nearly 38% of all IT environments are currently on the cloud and are expected to reach 59% in 1.5 years. This surge in cloud computing is expected to open a wide range of avenues for data engineers and catapult their demands.
Data has pioneered into new-age sectors like artificial intelligence, machine learning, and Big Data and is expected to have a huge impact on the way companies do business. If you upskill and become an expert in data science, upGrad’s online data science programs can definitely help you dive deeper into the world of data and analytics.
Considering this rapid growth in demand, data engineers are compensated handsomely across industries. However, there are several other factors influencing the data engineer’s salary. Let us get into further details about data engineers and their remuneration.
What does a Data Engineer do?
Data Engineers are vital for an enterprise to collect, process, and develop algorithms for raw data to make it resourceful. They optimize how data is collected and processed. They also handle the process of retrieving data, creating dashboards, generating reports, and other relevant documents.
The primary responsibilities of data engineers include:
- Designing data infrastructure
- Building data
- Arranging data pipelines for Data Scientists.
- Accumulating and segregating data for functional and non-functional requirements.
Data engineers are required to have a wide range of technical skills like programming, automation, and database design for efficient data processing. In some organizations, they are expected to communicate the data trends.
Their roles are focused on three specific interests:
- Generalist: The role of a generalist is seen in smaller companies where the data engineers are required to play several roles. Generalists take care of each step in the data process, starting from managing to analyzing.
- Pipeline-centric: This role is seen in medium-sized companies where data engineers associate with data scientists to interpret the collected data meaningfully. Pipeline-centric data professionals must have a stronghold on computer science and distributed systems.
- Database-centric: In huge companies where there is a constant flow of data, data engineers switch to analytic database systems. Database-centric data engineers work on multiple databases and generate table schemas for development.
Data Engineer Salary: How much does a Data Engineer earn?
As per Payscale, the average salary of a data engineer is $92,496 per annum. The compensation ranges between $65,000 to $132,000 based on the location, experience, levels, and skills of the data engineer. For instance, data engineers at the senior levels are offered $1,48,216, and those at mid-levels or level 2 are paid $116,591 per year.
A study suggests the demand for data engineers has been growing since 2016. As one of the fastest-growing domains in data science, data engineering witnesses approximately 50% growth every year in job opportunities. There was an 88.3% surge in job listings in 2019 alone.
Factors affecting the salary of Data Engineers
While there is no doubt that most organizations — large, medium, small, and startups — are willing to offer competitive compensation packages to data engineers, these professionals can enhance their earning potential in a number of other ways:
The years of experience that a data engineer brings to a job play a key role in determining his compensation. An entry-level data engineer is offered a starting salary of $90,615 per annum in the US while, on average, they earn about $108,291 per year. Senior-level data engineers, on the other hand, can earn an average of $124564 per year, with the base salary hitting nearly $179k at some companies, depending on their skills and certifications.
Data Engineers usually possess a degree in computer science, electrical engineering and have business studies as their major. According to reports, 61% of data engineers possess a bachelor’s degree while 21% have a master’s degree.
Data engineers with a master’s degree from renowned institutions are given more preference and offered higher compensations. An Executive PG Program in Data Science can also increase your earning potential and make you eligible for sought-after roles.
A lot of companies look for data engineers with a diploma in certified data engineering courses like Cloudera, Google Cloud Certification, CPEE (certificate in Engineering Excellence), and IBM certification. Data Engineers with knowledge in SQL, Python, Big Data, Apache Hadoop, and ETL have a high demand in the market.
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Compensation packages for data engineers also vary depending on their roles and positions in an organization. Let us look at different roles you can pursue as a data engineer:
- Data Analyst: The primary roles of data analysts include procuring, analyzing, and interpreting data to make them resourceful. They also help the clients with minor business decisions with the help of advanced computerized models that help in comparing data and predicting outcomes. The base salary package of an entry-level data analyst is $67,492 per annum as against their senior counterparts, who earn $84,295 annually.
- Business analyst: Business Analysts help companies improve and scale their operations by studying their business models in detail and upgrading them with new technologies to keep in tune with the current market trends and expectations.The package offered to a business analyst can range between $69,536 – $86,509 per year based on the years of experience. Interviews for business analysts saw a 20% increase in 2020, thereby substantiating their growing demand.
- Data Architect: Data Architects generate drafts for data management. They architect a plan to collaborate, centralize, safeguard, and maintain a company’s data sources after a detailed analysis. Data architects are paid an average of $121198 per year. Naturally so, data architects at the entry-level are paid less than those at the top of the hierarchy.
Different levels in data engineering correspond to their experience, roles, and overall command in the workplace. Data engineers at higher levels on their career ladder earn significantly higher than those at entry levels.
- Data Engineer I: $109K
- Data Engineer II: $121K
- Data Engineer III: $127K
- Principal Data Engineer: $151,886
(Salary Source – Glassdoor )
In companies where a data engineer performs the additional role of a manager, i.e., if they transition to the managerial track, they are offered a higher compensation.
The salary of data engineers also varies with their demand in different industries. Retail, media, and technology sectors are leading industries where data engineers are highest in demand and are compensated accordingly. These are followed by finance and professional services companies.
The following list provides the details of the industries and the corresponding average packages offered to data engineers:
- Retail: $114,152 per year
- Media: $112,864 per year
- Technology: $105,173 per year
- Professional Services: $98,633 per year
- Finance: $82,262 per year
Here is the list of top companies and their packages offered to data engineers.
- Amazon: $123,736 per year
- Hewlett-Packard: $86,164 per year
- Facebook: $134331 per year
- Google: $161544 per year
- IBM: $107951 per year
Different cities also offer lucrative packages to data engineers depending on their demand and earning potential. It is estimated that cities like California, Washington, New York, New Hampshire, and Massachusetts offer the highest salaries to data engineers. As per Hired’s State of Software Engineer’s report 2019, the average package of data engineers has grown by 7% in New York and 6% in the Bay Area.
Data Engineering is an amalgamation of software engineering and data science. A data engineer with strong knowledge in each of these disciplines is hired by leading companies. In addition to these two, data engineers are also required to be well-versed in programming languages like PHP, Scala, R, Go, and other relevant languages.
These skills offer leverage to data engineers for salary negotiations and can fetch an additional 10-15% in the salary package. As per PayScale, the following skills provide a considerable boost in the package:
- Scala: 17%
- Apache Spark: 16%
- Data Warehouse: 14%
- Java: 13%
- Data modelling: 12%
- Apache Hadoop: 11%
- Linux: 11%
- ETL: 7%
- Amazon Web Services (AWS): 10%
- Big Data Analytics: 6%
Future Scope of Data Engineering
As per the 2020 technical job report by DICE, data engineering is the most rapidly growing sector, having witnessed a 50% year-over-year surge in job opportunities between 2019 and 2020. In addition to this, the earning potential of data engineers is further expected to increase since most companies are shifting to the cloud. Not to mention, data engineering has surpassed data scientist roles by 2:1, and companies now pay them 20-30% more, something that is bringing data engineers closer to being tagged as the highest paid professionals in the technology sector.
The following statistics by popular tech platforms reveal a consistent growth in data engineering:
- The Hired State of Software Engineers Report shows a 45% year-on-year growth in the domain.
- LinkedIn’s Emerging Job Report recorded a 33% year-on-year job growth.
- The Burning Glass Nova Platform reports a 88% year-on-year growth in data engineering jobs.
These are indicative of the rapid pace at which data engineering is overtaking the data science sector.
Following the heavy influx of data scientists in industries, companies have realized the importance of a regulated data infrastructure to provide effective data analysis. So, businesses are now spending time and effort to hire data engineers who have a sound understanding of systematic cloud infrastructure and data architecture.
Big data engineering services in companies like Accenture and Cognizant have led to an 18% yearly growth in the market and are expected to reach 31% by 2025.
Transform your career with upGrad’s online Data Science Programs
Considering the impressive trend for data engineering and that the position is well-positioned to be the next massive thing in the tech industry, there hasn’t been a better time to upskill yourself to land a lucrative position in data science.
And upGrad offers a unique opportunity to transform your career with its Executive PG Programme in Data Science from IIIT Bangalore. It is a 12-month course that teaches you highly sought-after skills like Python, Tableau, Apache Hadoop, AWS, and MySQL, among others.
In addition to this, students stand to learn industry-relevant skills through specialization tracks which include Data Science Generalist, Deep Learning, Natural Language Processing, Business Intelligence/Data Analytics, Business Analytics, and Data Engineering.
The course is designed for freshers and mid-level managers who can engage in collaborative projects on the global platform and indulge in peer-to-peer learning with students and mentors from diverse backgrounds.
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