After 12th grade, students spend considerable time deciding on their careers. The competitive job market often drives students to choose careers that offer growth potential, lucrative salaries, and respect. In that regard, data engineering is becoming a popular profession.
Companies heavily depend on data to predict their profits and losses or to improve their products and customer experiences. But how do they gather the data? That’s when data engineers come to play.
These professionals collect, organise, and store raw data to provide businesses with valuable insights into their products, customers, and more. The shift to a data-focused world makes data engineering a valuable career.
In fact, it is one of the fastest-growing tech jobs, with exposure in India and abroad. Combining relevant technical and soft skills will advance data engineers’ career paths. That way, they can earn higher salaries and secure more advanced positions.
If you also aspire to be a data engineer, you may have a question in mind: Is a data engineer a good career?
This blog will answer your query and outline the roles and responsibilities of a data engineer. Furthermore, it will discuss career opportunities as a data engineer, the salary structure, and the future scope of the role.
Key Takeaways
To become a data engineer, you should know the key facts. These are as follows:
• A data engineer tackles various responsibilities, including data collection, data cleaning, and collaboration.
• Big data engineers, streaming data engineers, and data warehouse engineers are major types of data engineers.
• The salary range for data engineers abroad can be between $90,000 and $130,000 annually, depending on the role.
• Python, Data Modelling, and Version Control are core technical skills in the field of data engineering.
• Amazon, LTIMindtree, and Meta are top companies for data engineers in India and abroad.
What is a Data Engineer?
Data engineers are IT (Information Technology) professionals who acquire, store, transform, and manage data in an organisation. They are responsible for managing the design, creation, and maintenance of data processing systems and database architecture.
Their job allows data analysts and scientists to analyse and visualise the development of machine learning models. Through such development, data analysts and scientists extract valuable insights for better decision-making.
In short, data engineers act as a bridge between raw data and actionable insights. To understand data engineers better, here’s an overview of what they do:
| Tasks | Description |
| Data collection | Acquiring data from multiple sources: websites, applications, and systems. |
| Data cleaning | Removing errors and fixing missing data. |
| Data storage | Saving data in cloud systems or databases. |
| Build data pipelines | Designing and creating ETL (extract, transform, and load) pipelines. |
| Collaboration | Working closely with data analysts, data scientists, and software engineers. |
Difference Between a Data Analyst and a Data Engineer
In a data-driven role, you may encounter the terms data engineer and data analyst. Both are crucial for gathering insights from data; however, they differ in focus, career paths, and work styles.
The focus of data engineers is on building and maintaining data infrastructure. Data analysts, on the other hand, interpret data from the infrastructure to answer business questions.
Data engineers mainly perform technical jobs. Their work is heavily focused on managing data systems, cleaning data, and sending it for interpretation.
It is the job of data analysts to obtain the refined data and process it for visualisations. They create dashboards and reports, making the work more presentation-centric.
The career paths for data engineers usually start as junior engineers and progress to Machine Learning (ML) Engineer or Platform Lead. For data analysts, career opportunities begin as a junior analyst, and with skill development, you can move into more strategy roles.
How to Become a Data Engineer?
The increasing demand for data infrastructure in businesses is unlocking opportunities for data engineers. Students who want to explore the new-age profession often ask: Is data engineering a good job?
The answer is yes. As cloud computing and big data continue to grow, so is the demand for skilled data engineers. To become a data engineer, it is essential to have a strong foundation in programming languages and databases. Moreover, here are other tips that can help you enter the field with confidence:
• Develop a foundational knowledge in applied mathematics, IT, or computer science to understand data principles.
• Learn about cloud platforms, with a focus on SQL (Structured Query Language) and Python as primary technologies.
• Create a portfolio to present your skills and knowledge in real-world scenarios. It may include end-to-end projects such as a real-time data ingestion system and a data processing pipeline.
• After demonstrating your skills through a portfolio, validate them with certifications. You can acquire the Google Cloud Certified Professional Data Engineer badge to demonstrate your credibility.
• Start entry-level positions as a junior data engineer to test your core knowledge and skills. It will help you move up to better positions as you develop more skills.
What Are the Roles & Responsibilities of a Data Engineer?
After learning the tips to become a data engineer, you may be wondering about the roles and responsibilities. The core function of a data engineer is to collect and organise raw data, which is then visualised and interpreted.
Additionally, data engineers play crucial roles by providing technical expertise and transforming data. These roles and responsibilities of data engineers are as follows:
• Building data pipelines: Data engineers design and create data pipelines and aggregate them from different sources. These pipelines then collect and move data to predetermined storage locations, like transportation systems.
• Data transformation and cleaning: Every piece of data is unique. Data engineers are responsible for integrating, consolidating, and cleaning data. As the data transforms, the engineers render it, making it useful for analysis.
• Technical expertise: Data engineers are good with technology and tools. They use Python and Java to develop database management system code. Furthermore, they are well-versed in data modelling and cloud platforms like Google Cloud and AWS (Amazon Web Services).
• Working as a team: Data engineers don’t work in isolation. They work with data analysts, data scientists, and other stakeholders to understand data requirements. Also, they help align that data with the organisation’s goals, allowing users to get valuable insights.
Types of Data Engineers
The diversity in data engineers’ responsibilities reflects different types of data engineers. While warehouse engineers focus on data modelling and storage, big data engineers manage distributed databases using different technologies.
Other than that, there are also other types of data engineers that you will find out:
• Data pipeline engineers: These data engineers build, automate, and maintain pipelines to move and transform data. Students who are keen on mastering ETL can explore opportunities as these engineers.
• Big data engineers: As a buzzword, students wonder whether a big data engineer is a good career choice or not. The truth is, if you want to manage very large datasets, it can be a good career. For that, you must learn technologies like Spark and Hadoop.
• Machine learning data engineers: They bridge the gap between data engineering and data science by creating robust datasets for ML models. Individuals who want to gain expertise in both data science and data engineering principles can specialise as these engineers.
• Streaming data engineers: They are professionals who handle real-time data. Their roles include processing data in motion to gain almost instant insights.
• Data warehouse engineers specialise in designing, building, and optimising data warehouses. Moreover, these professionals also structure data for complex analytical queries.
Data Engineer Skills and Qualifications
No matter what type of data engineering path you want to specialise in, it is crucial to have relevant skills and qualifications. Since a data engineer focuses on technology, it makes it one of the best career options after 12th science.
To qualify as a data engineer, you should have an undergraduate degree in computer science or a related discipline. It will help you get a strong foundation in computation and data.
Moreover, you can obtain certifications like AWS Certified Data Analytics and Google Cloud Professional Data Engineer to qualify as a professional. It will make your career path credible and advance you to higher positions.
With all these qualifications, you should also have technical and soft skills. It will help you make a good career as a data engineer:
• Database management
• Data modelling
• Python
• Version Control
• Problem-solving
Career Opportunities in Data Engineering
Businesses these days rely on data, regardless of industry. From healthcare to finance, every sector is looking for data engineers to turn raw data into actionable insights.
Using different skills, these professionals build data pipelines and transfer them to desired locations for interpretation. Different industries offer various career opportunities for data engineers, including Big Data Engineer, Data Architect, and ETL Developer roles.
To understand data engineer career options in different sectors, here is an industry-wise list:
• Technology & IT Services: Professionals will focus on product analytics and manage massive user datasets. Career paths in technology and IT as a data engineer include ML Engineer and Data Architect.
• Banking, Financial Services & Insurance: The data engineering principles are essential in risk analysis and fraud detection. Data Pipeline Engineer and Cloud Data Engineer are common career paths for data engineers in this field.
• E-commerce & Retail: Data engineers using their knowledge optimise supply chains and personalise customer experiences. The career options in e-commerce as a data engineer include ETL Developer and ML Engineer.
• Healthcare & Pharmaceuticals: The businesses use actionable data to manage patient records and clinical trial analytics. Clinical Data Engineers and Health Information Systems Developers are promising career paths in healthcare.
• Manufacturing & Logistics: Supply Chain Data Engineers and Logistics Technology Specialists play a crucial role in data processing. The industry demands these professionals to ensure predictive maintenance and supply chain automation.
Who Should Choose Data Engineering as a Career?
The growth potential across industries makes a career in data engineering a good choice. But the real question is: who is it best suited for?
Usually, individuals with backgrounds in computer science or software engineering find data engineering a rewarding career. The disciplines provide a foundation in data, computation, and programming languages that are essential for pursuing a career as a data science engineer or data engineer.
Moreover, data engineering is a suitable career for individuals who:
• Love organising, collecting, and processing large datasets.
• Look to specialise in data-driven backend systems.
• Like to tackle complex technical puzzles and ensure data is accessible.
• Enjoy designing data infrastructure and pipelines.
Data Engineer Salary in India & Abroad
After understanding your passion for data engineering, you may want to look at the earning potential. As a data engineer, you will get lucrative salaries in India and abroad due to the high demand for data infrastructure in varied industries.
However, the average salary of a data engineer in India differs significantly from that abroad. Also, skills and job roles play an important role in determining data engineers’ salaries.
Data Engineer Salary Based on Skill Set
Data engineering, like other branches of data science, is skill-driven. Aspiring professionals should combine both technical and soft skills to earn promising salaries.
In India, students with expertise in SQL, Python, ETL tools, and cloud platforms can earn between INR 4 LPA and INR 12 LPA (entry-level). The range scales up as you deepen your understanding of these programming languages and cloud platforms, offering around INR 50 LPA (senior-level).
In countries like the United States, Australia, and Canada, salaries are much higher. It often exceeds six figures, with an annual salary of $100,000. Having a strong skill set will help you earn more as you move to senior levels.
Data Engineer Salary Based on Role
Keeping the skills in mind, you can decide on your role as a data engineer. For instance, you work as an Azure Data Engineer. The skills that you derive from the cloud computing platform will help you get into certified roles. As a result, you can earn between INR 10 LPA and INR 14 LPA.
In foreign countries, with greater scope for data professionals, salaries can be higher. Working as the same engineer, you may earn $90,000–$130,000 annually.
Top Companies Hiring Data Engineers in the USA
As you understand the salaries based on skills and roles, it’s time to learn about the recruitment opportunities. Foreign countries, especially the USA, offer huge data infrastructure. It thus allows aspiring professionals to explore the country and work in top companies.
The following are the companies in the USA that unlock career opportunities for data engineers:
• Amazon (AWS)
• Meta (Facebook)
• Microsoft
• Oracle
• Accenture
Top Companies Hiring Data Engineers in India
Many tech giants from abroad have branches in India for data engineers. If you wish to stay in India and demonstrate your role as a data engineer in different industries, there are various companies available. These are as follows:
• Infosys
• Wipro
• Tata Consultancy Services (TCS)
• LTIMindtree
• NTT (Nippon Telegraph and Telephone) Data
Key Factors Influencing Data Engineer Salary
Once you learn about the top organisations for data engineering, you may wish to learn about the salaries that they are offering. Whether the company is located abroad or in India, certain factors will influence it.
These factors include industry, experience, company size, education, and skills. Let’s explore them to understand the salary difference better:
• Industry: The amount of data processing taking place in the technology, healthcare, and finance sectors is more than in the other sectors. As a result, data engineers’ salaries in these sectors are higher.
• Experience: Data engineers with more experience have higher earning potential than fresh graduates.
• Company size: Tech giants and well-known companies offer more earning opportunities for data engineers than small startups.
• Education: Data engineers with specialised courses or advanced degrees can command higher salaries.
• Skills: Aspiring data engineers with strong proficiency in technical and soft skills, including SQL and Python, have more earning potential.
Why is a Data Engineer a Good Career?
The passion for data collection and organisation is a driving force to become a data engineer. But, with a vast scope of data science, why choose a career as a data engineer?
Here are the reasons to choose a data engineer as a career option:
• The increasing demand to handle massive datasets makes data engineering a vital profession.
• Data engineers collect and clean data, which then goes to data analysts and data scientists for interpretation.
• The high skill set level makes data engineering a well-paying career. However, the salary also depends on your experience level and the industry you’re serving.
• Data engineers allow a smooth career transition as you develop skills. It helps you to make a switch from a basic data engineer to a data architect.
Where to Learn Data Engineering in India?
After assessing data engineering as a good career, it’s time to understand the discipline’s core. For that, you should know the institutions that are offering undergraduate/post-graduate programs in data engineering.
In India, there are different government and private colleges and universities offering a myriad of engineering programs.
These are as follows:
• Indian Institute of Technology (IIT) Madras
• Indian Institute of Technology (IIT) Hyderabad
• Indian Institute of Science (IISc) Bangalore
• Institute of Data Engineering, Analytics and Science Foundation, Kolkata
What’s the Future of Data Engineering?
As the world of data continues to grow, data engineers play a crucial role in shaping the future. In such a scenario, the discipline is closely linked to data science. Thus, people often ask: Is data science engineering a good career?
The answer is yes. And there are various trends that data engineers can use to find better opportunities:
• Cloud-based solutions: Cloud platforms will continue to offer flexibility. It will thus allow data engineers to use these platforms for more data engineering projects.
• Automation: Data pipeline maintenance is a repetitive task. With Artificial Intelligence (AI), data engineers can automate these tasks, freeing up more time to collect and organise raw data.
• Data democratisation: Data engineers will offer their expertise in developing user-friendly interfaces and tools. Using these tools, businesses can access refined data to make informed decisions.
How Career Planner Helps You Start a Career in Data Engineering?
The demand for accurate and consistent data across industries makes data engineering a core discipline. But as extracting, sorting, and collecting data are still relatively new concepts, students wonder whether a career in data engineering is a good choice.
Indeed, it is a good career, especially if you’re passionate about coding, solving technical challenges, and collecting raw data. But to perform all of these, you need strong data engineering skills.
As someone who just completed 12th grade, you may find it challenging to decide on a career as a data engineer. That’s when Career Planner steps in. We help you connect with industry experts who will guide you through the process.
Our aim is to help you analyse your interests and find suitable career options in this field. As you pick your career, the key part follows. That involves finding the right course and institutions for the discipline. With our educational fair, you can even get a clear picture of them and start your data engineering career.
Connect with us to begin your career as a data engineer.
FAQs
What is the salary of a data engineer in India?
The salary of a data engineer is highly competitive in India. It ranges from INR 4 LPA to INR 30 LPA, depending on experience level, skills, and role.
Are data engineers in demand?
Yes, data engineers are in high demand as jobs worldwide are growing. As businesses now implement AI and big data into their operations, demand for these professionals is also rising.
Is a data engineer a high-paying job?
Yes, the need for data infrastructure in AI and analytics makes a data engineer a high-paying job. It also offers high growth potential as you develop both technical and soft skills. These include programming languages, data modelling, and problem-solving.
What does a data engineer do?
A data engineer designs, builds, and maintains databases or data pipelines. They work in various settings to transform raw data into useful information. Data analysts and data scientists then use the information they gather to interpret it.
Will a data engineer be replaced by AI?
No, AI will not replace a data engineer. Rather, it will transform the way these engineers code. AI will shift data engineering from manual coding to automated orchestration, eliminating repetitive tasks.
Is data engineering a lot of coding?
Yes, data engineering requires significant coding in Python and SQL. Using these programming languages, data engineers create code to build data pipelines.
