The State of Data Engineering in India: 2024
Data engineers are primarily responsible for the collection, storage, and analysis of the data. They are responsible for converting the data that can be used by the data scientists, for the analysis of the dataset. They are also responsible for data collection, data transformation, data storage, data integration, and automation of the pipeline of the data. With the advent of digital technologies, a significantly large volume of data is being generated. The data is generated through several sources including sensors, transactions, social media, and others. Data engineers play a vital role in managing the data and ensuring its quality and integrity. Data Engineers are the professionals who create pipelines to transform this data into formats that data scientists can read and use to further analyze the datasets. This data pipeline entails collecting data from various sources and storing it in a single warehouse, where it will be represented uniformly. The first section of the report provides an industry overview of the data engineers in India. It highlights several aspects such as salaries and number of the data engineers across several sectors. The next section provides an overview of job openings for data engineers, and also provides a detailed description of the information on the number of job openings by sector, by salary bracket, in different sectors, and based on the size of the company. Furthermore, it also highlights the job openings by work models, and by company size. The report also covers information on the number of data engineers on the basis of geography, roles, skills required for data engineers and on the basis of the work models. Moreover, the report also provides a detailed analysis on the attrition rates for data engineers across India. It also projects a picture on the attrition rates of data engineers. Furthermore, the report highlights the key skills of data engineers in the present market. The report concludes with the distribution of data engineers by different roles in India. Key take away: Generative AI is revolutionizing data engineering by significantly accelerating the transformation of raw data into actionable insights. For previous year’s reports: 2022 | 2023 Key Findings Senior Talent Demand: The proportion of data engineers with 6+ years of experience increased significantly across various sectors, rising from 27% in 2023 to 38% in 2024. This suggests a growing demand for senior-level talent in the field. Salary Growth: There has been a notable increase in the number of data engineers earning between ₹6-10 lakhs, which escalated from 24% in 2023 to 32.4% in 2024, marking an increase of approximately 8.4%. Job Availability: While precise figures are challenging to pin down, there were 10,593 job openings for data engineers across all industries found on online job portals. Attrition Rates: The overall attrition rate in companies decreased from 18% in 2023 to around 14% in 2024, indicating improved retention strategies and possibly better job satisfaction or market conditions. Sector-Specific Employment: In the non-IT sectors, the BFSI sector accounted for 49.3% of data engineer employment in 2024, highlighting a significant concentration of data engineering roles in this industry. Read the complete report here:
The market of data engineering in India is anticipated to expand at a CAGR of around 33.8% in the next five years growing from USD 29.1 billion in 2023 to USD 124.7 billion in 2028.
Discover the vital role of data engineers in managing and transforming large volumes of data generated by digital technologies. Learn how they collect, store, and prepare data for analysis, ensuring its quality and integrity. Explore industry insights into data engineers in India, including salary trends and sector-wise distribution. Understand their essential functions, from data collection to pipeline automation, enabling data scientists to extract valuable insights.
["Data Science"]
["AI", "ML", "data pipeline", "Scala", "Git", "RAG", "data engineering", "ViT", "generative AI", "Data Science", "R"]
["AI", "ML", "generative AI", "RAG", "R", "Scala", "Git", "data engineering", "data pipeline", "ViT"]
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