In October 2012, being a data scientist was considered the sexiest job of the 21st century. It kept its status as a proliferating profession for 10 years. This prediction perfectly forecasted a massive increase in demand for data scientist requirements as resources. This also paved the way for several start-ups and businesses that thrived by providing relevant training skills in data science.
The immense growth and potential of data engineering are growing 50% year over year. Let us learn more about the thriving data science career path and upscaling in data science roles.
What is data engineering?
Data engineering has become a buzzword, a trending skill, that is excessively in demand because of its value-add to businesses in the computer science discipline. Data scientists desperately need experts to manage and streamline data, and these skilled professionals are none other than Data Engineers.
Data engineering can be defined as the collection and validation of quality data that data scientists can successfully and extensively utilize. Data engineering has a wide scope, including data management, mining, infrastructure, processing, acquisition, and modeling.
It cannot be defined as a one-man's job, and thus various jobs in data engineering are available across the globe. All you need to do is acquire the relevant educational qualification and enroll in a data science certification course to fulfill the data scientist requirements.
Data engineering courses help you with large-scale data collection, storage, and analysis systems. Data engineering is applied in almost every industry, making life easier for data scientists. Do you know that 463 exabytes are predicted to be generated daily by 2025?
Digitalization and advancements in AI, specific fields like deep learning and machine learning cannot succeed without Data Engineers processing and channeling that data. E-commerce, Banking & Finance, Transport, Healthcare, Digital Marketing, and Retail are some of the most critical sectors that depend on data engineering processes.
Data engineering market and growth numbers
One estimate states that "Big Data Analytics" in the US manufacturing sector was worth USD 904.65 million in 2019. Furthermore, it is projected to grow to USD 4.55 trillion at a compound annual rate (CAGR) of 30.9% during the 2020-2025 forecast period.
Let us look at some growth numbers of Data engineering in India
The Indian data engineering market is estimated to be $18.2 Billion in 2022. It is expected to grow at a CAGR of 36.7% over the next 5 years and is predicted to reach USD 86.9 billion by 2027. India's banking/insurance sector employed the highest percentage of Data Engineers of any non-IT industry at 37.7%.
Scope of the job data engineering market
Building a data science career path in data engineering is challenging, worthwhile, and very much in demand. The scope of the job market in data engineering is massive as it leads to convenient access to data scientists, analysts, and decision-makers of organizations.
As long as there is data to be processed, there will be a demand for Data Engineers. Data engineers get rewarded with one of the best salaries for data scientist requirements in India.
Start your data science career path with a relevant degree in computer science or a related field. Earning a bachelor's degree will help you build the knowledge foundation you need in this rapidly changing field. Consider a master's degree for higher-paying positions.
Enroll in a data science certification course and be ready for the expansive job market of data engineering. Here is a step-by-step procedure that can help you take full advantage of the scope of the data engineering job market:
Step 1 - Develop your data engineering skills by working on fundamentals like coding, cloud computing, and database design. Hero Vired offers a Certificate Program in Data Engineering that empowers you with skills and sharpens concepts related to the job. You should be sound in concepts like:
- Relational and non-relational databases
- ETL (extract, transform, and load) systems
- Data storage
- Automation and scripting
- Machine learning
- Big data tools
- Cloud computing
- Data security
Step 2 – Find India's best data engineering courses and get certified.
Step 3 - Build a portfolio of data engineering projects.
Step 4 - Start with an entry-level position
What does a Data Engineer do?
Let us understand the key job responsibilities of a data engineer:
- Data engineers support business applications by advancing the process of artificial intelligence analytics and machine learning.
- A Data Engineer collects, designs, and manages the data sources essential to business insight to build a data engineering architecture.
- Data Engineers need to master programming languages such as Python and Julia and have a deep knowledge of SQL and XML to work on data management systems and data infrastructure while complying with all data management standards.
- Data engineers optimize database speed and prevent workflow interruptions by working in various environments.
- The ultimate goal of Data Engineers is to make data accessible to data scientists and key stakeholders of a business so that they can make informed decisions.
- Other key responsibilities include getting the right datasets for business needs, formulating algorithms to turn data into useful insights, creating & testing the architecture of the database pipeline, and collaborating with the management to understand business goals.
Skills needed for data engineering
Data engineers collaborate with data scientist requirements and business leaders as part of an analytics team to improve operations. Data engineering is a skill that is increasingly in demand and helps various industries in:
- Business acquisition.
- Searching all the different datasets related to the business.
- Finding and eliminating errors in the data.
- Providing a common format for all data.
- Interpretation of data that can be interpreted in different ways.
- Removing duplicate copies of data.
Data engineers also manage the data warehouse, which is used to copy, move and store subsets of data. That said, the key areas of expertise and the appropriate skillset required by Data Engineers would be:
- Fundamental of software engineering
- Distributed systems include skills as a software engineer and software architect.
- Open frameworks
- Programming – need appropriate knowledge of Python, Java, Scala, etc.
- Cloud platforms
- Analytical approach with various mathematical principles of probability to properly manipulate data.
- Data modeling
- Structure tables and partitions, where data will be normalized and denormalized in the warehouse
Types of job roles in data engineering
Data engineers' scope in the job market varies depending on their industry and company. They can be divided into three categories: database-centric, pipeline-centric, or generalist.
- Generalist: Generalist Data Engineers usually work in small teams with scientists and analysts with data science expertise. Data engineers who are the sole data-focused employee at work will often need to be more involved in the end-to-end process, including ingesting, processing, and analyzing the data.
- Pipeline-centric: Larger, mid-sized data science companies in India often have pipeline-centric Data Engineers. They work with data scientists to interpret and utilize the data.
Larger data science companies in India often have more complex needs than Data Engineers who are generalists. Because their work involves a deep understanding of data systems and computer science, they often work in teams.
- Database-centric: Database-centric Data Engineers can be found in the most prestigious data science companies in India and conglomerates. Their job is to create and populate analytics. Data engineers are often responsible for large databases and work with multiple data warehouses.
Here are the best data science roles in data engineering that are varied and can be classified as the following:
- Business Intelligence Developer
- Data Architect
- Applications Architect
- Infrastructure Architect
- Enterprise Architect
- Data Analyst
- Data Scientist
- Data Engineer
- Machine Learning Scientist
- Machine Learning Engineer
Salaries of data engineering jobs
- The highest proportion (30.8%) of Data Engineers have 3-6 years of work experience with an average salary of INR 17 lakhs per year. A data scientist's salary in India with 1 to 4 years of experience is approximately INR 610,811 per year.
- Data engineers in the IT/e-commerce industry have the highest average salary of INR 28.5 lakhs per year. Data Engineers working in New Delhi earn the highest average salary of INR 19.3 lakhs per year, followed by Bengaluru with INR 19.0 lakhs per year.
- Lately, in the last week of May 2022, open positions for Data Engineers were reported at 36,457.
- More than two in five jobs (44.9%) are listed for Data Engineers with between 5 and 10 years of experience.
- More than 9 out of 10 Data Engineers (92.0%) can work with Python. Data engineers are well-equipped with other popular skills in cloud usage (30% of engineers can work in Azure) and SQL.
- In terms of cloud usage, more (39.0%) professionals can work in Azure than in other technologies.
- SQL is the most popular programming language among Data Engineers with 0-3 years of experience, 100.0% of whom can use it.
- AIMResearch estimates that the share of data engineering in the analytics market will increase from 29.8% in 2022 to 43.2% in 2027.
Best cities in India for data engineering jobs
Data generation, accumulation, analysis, and usage is increasing at an unimaginable speed, and jobs in data science roles and data engineering are some of the most sought-after professional fields in the world. MNCs and businesses of all kinds and scales are looking for data scientists, engineers, and professionals.
Working in cities like Delhi, Bangalore, Mumbai, and Chennai have welcomed and incorporated thriving tech data science companies in India, which hugely demand Data Engineers.
Delhi/NCR has reported an increase in 22% of data engineering-related analytics jobs in India, followed by Mumbai at 15% and Chennai at 7%.
Delhi also offers the highest average pay scale for Data engineers, which is INR 9.3 lakhs per year. Bangalore and Mumbai follow with INR 19 lakhs and INR 17.5 lakhs per year, respectively. Chennai offers the lowest average salary at INR 14.8 lakhs per year.
Salary of data scientists in India in the top four Indian cities(annually):
- Data scientist salary in India - Bangalore: INR 984,488
- Data scientist salary in India - Pune: INR 725,146
- Data scientist salary in India - Mumbai: INR 788,789
- Data scientist salary in India - Hyderabad: INR 795,023
Let's look at the future of data science roles in India that could soon become a reality.
- The Internet of things (IoT), which connects intelligent devices, is already a reality. However, we can look forward to being part of an Intelligent Digital Network, a connected hub of apps, computers, and people working together in the future.
- Advanced chatbots, virtual reality (VR), and augmented reality (AR) will transform product marketing and customer services.
- Blockchain is not limited to the financial industry. It can also be applied to healthcare, banking, and insurance.
- Together in the future of data science in India, augmented analytics and automated machine learning systems will transform predictive analytics. This aspect will help change the face and future of healthcare.
- It is predicted that there will be more than 11,000,000 Data science jobs in 2026 as technology, data science, and AI advance.
As clear from the above discussion, data engineering is a thriving profession and a critical credential in your data science career path portfolio. You should equip yourself with the right education, expertise, techniques, learning, experience, and the best certification in India. This will help you do your job well.
Hero Vired offers a Certificate Program in Data Engineering and other data science certification courses. You can learn with an industry-specific data engineering tool. A dedicated Program Manager from the learning platform will assist you with your questions, discussions, Forums, and Community.
The program introduces advanced SQL queries that allow you to extract relevant data from business problem statements. You learn how to transform data into valuable dashboards or designs for data analysis and reporting, and you understand data pipelines and how they are deployed on cloud infrastructure.
Become a certified Data Engineer today and advance your data science career path and your potential as a data engineering professional, which is the future of data science in India.
Thanks to their extensive knowledge, Data Engineers can be seen working with Database Administrators, Data Scientists, and Data Architects. So, add a feather to your flourishing career and get certified as a Data Engineer.