Today, we will be exploring the following topics in this blog, starting with an overview of Big Data and then eventually discussing the Big Data Engineering salaries in India.
The salary of a Big Data Engineer is incredibly higher than most job roles in the industry. However, various factors come into play while determining the salary. In this Big Data Engineer salary blog, we will discuss the salaries of these professionals working in India, especially some of the popular cities in India, and see how the salaries vary according to experience.
Learn how you can become a Big Data Engineer from Intellipaat:
Big Data: Overview
Big Data is characterized by the volume, variety, variability, and velocity of data, which makes it critical to have someone with the right knowledge to handle it. The fact that the world will never run out of data creates plenty of opportunities for Big Data Engineers around the world to meet the demands of enterprises and receive significant compensation for their services. While that is understandable, let’s take a look at what a Big Data Engineer actually does as part of their job.
What does a Big Data Engineer do?
Big Data Engineers have the necessary skills to work with enormous arrays of complex datasets. Ever since the dependency on databases has grown, the role of Big Data Engineers has become pivotal in the management and handling of data systems and tools.
Big Data Engineers are responsible for the utilization of available data and technologies to build a data landscape for Data Scientists. Data Engineer and Data Scientist, you need to keep in mind that both roles have their own importance in the field of Analytics. A Big Data Engineer’s knowledge goes beyond the data that is available in the company and its storage locations and also extends to data integration into the central analysis infrastructure and identifying suitable technologies that can be used.
Big Data Engineer Tasks
A Big Data Engineer’s work starts with the understanding of the technical requirements and then moves to the planning and development stage to build a flexible but robust infrastructure. They work on data collection, storing, processing, and analysis. To frame it in simple terms, a Big Data Engineer makes crucial data easily accessible and usable across multiple departments of an organization.
Acquire all the required Big Data skills by enrolling in Intellipaat’s Hadoop Certification Course
Required Skills of a Big Data Engineer
Big Data Engineers need to have knowledge of programming languages, databases, and data processing tools in general. Let’s quickly take a look at the top skills of a Big Data Engineer.
Machine Learning (ML) is one of the quintessential skills that can lead to a successful Big Data career. Machine Learning makes sorting and processing large volumes of data easier and quicker, and not to mention, Big Data helps in building Machine Learning algorithms as processing datasets is part of the ‘learning’ process. Big Data Engineers are expected to have knowledge of writing algorithms and using them during data ingestion.
Database skills and tools
Data storage, searching, and organization is all at the core of databases. Hence, it is extremely crucial to understand the structure and language of databases. There are two primary types of databases—SQL-based and NoSQL-based. NoSQL databases have become increasingly popular and include a key-value cache (Coherence, Ignite, and Hazelcast), object database (ZopeDB and Prest), tuple store (Apache River), a key-value store (Aerospike), document store (IBM Domino, BaseX, and Clusterpoint), wide column store (Amazon DynamoDB and Cassandra), and native multi-model database (MarkLogic and Cosmos DB).
Hadoop consists of a series of open-source libraries used to process huge datasets over large numbers of servers and devices simultaneously. Depending on the data and the mode it runs in, Hadoop has varying degrees of scalability. Data Engineers should be familiar with the modes and the purpose of each. They should also know which tools are available to them and where Hadoop is applicable in a dataset.
Java is a major skill of Big Data Engineers and one of the widely used coding languages for building Machine Learning sequences and data sorting algorithms. Big Data Engineers are also expected to be skilled in writing automated scripts and Java Machine Learning libraries like Java ML.
Due to its versatility and easy learning process, Python is another popular programming language. Python has a series of libraries as well as a widespread community. Big Data Engineers are thus required to be proficient in this language and build tools with it. They should also be involved in the contribution to Python libraries and draw value from them.
Apache Kafka is a community-distributed processing software platform that uses Java and Scala. It can work with real-time data feeds and connect to external processing libraries. Big Data Engineers are required to have knowledge of its architecture, usage, and its integration with other libraries.
Scala is a concise programming language and is used in data processing libraries like Kafka. It depends on a static-type system and almost acts as a counterpart to Java. It includes additional libraries for Big Data Analytics and Machine Learning, such as Spark MLlib (Machine Learning), Spark SQL, Spark Streaming, and Spark GraphX (graph analytics).
Clouds play a huge role in storing and processing data. It offers distributed access and high scalability compared to on-premises servers. So, Big Data Engineers will find themselves working with Cloud Computing more often. Some popular types of cloud services for Big Data are AWS, Azure Data Lake, and Google Cloud. Engineers are required to be knowledgeable in the cloud storage types, their security levels, and the tools made available by various cloud service providers.
Apache Hive is a data warehouse software built on top of Hadoop for the purpose of data queries. Its operation is like SQL and allows indexing, user-defined functions, and metadata storage. Big Data Engineers have to know how to query Hive, its architecture, and the primary languages such as Python and Java that it uses.
Apache Spark functions as a major open-source tool that is used by Big Data Engineers. It is used for huge datasets as a distributed cluster-computing unified analytics engine. Spark serves as a programming interface for programming clusters. Big Data Engineers are expected to know operations on the frontend (SparkR), on the backend, Spark libraries, and Spark cluster. Intellipaat’s Spark Course is designed in line with industry experts to help you become a certified Big Data Engineer.
Check out our blog on Hadoop Tutorial to learn about the concepts involved in the Big Data domain.
Roles and Responsibilities of a Big Data Engineer
- Raw data collection and processing at scale
- Implementing suitable tools and frameworks for the design and development of data applications
- Data reading, extraction, transformation, staging, and loading to tools and frameworks as per requirements
- Calling APIs, writing SQL queries, writing scripts, web scraping, etc.
- Coordinating with the engineering team for the integration of the Big Data Engineer’s work into the production systems
- Unstructured data processing to make it into a suitable form for analysis
- Processed data analysis
- Supporting business decisions with ad-hoc analysis
- Data performance monitoring and infrastructure modification as required
- Defining data retention policies
Big Data Engineer Job Opportunities
- There are over 2,000 job opportunities available for Big Data Engineers in India – LinkedIn
- There are over 16,500 jobs listed in total for Big Data Engineers in the United States – Indeed
Big Data Engineer job opportunities (according to LinkedIn) in various Indian cities:
- Bangalore: 1,160+
- Chennai: 190+
- Hyderabad: 330+
- Delhi: 300+
- Mumbai: 240+
Check out our blog on Hadoop Interview Questions And Answers.
Big Data Engineer Salary in India
According to Glassdoor, the average salary of a Big Data Engineer in India is ₹820,000 per year.
Below are some salary figures, according to PayScale:
An entry-level Big Data Engineer’s salary is around ₹466,265 annually. An early-career Big Data Engineer or a Junior Big Data Engineer’s salary (1–4 years of experience) is an average of ₹722,721 p.a. A mid-career Big Data Engineer or Lead Big Data Engineer salary (5–9 years of experience) is ₹1,264,555 per year. A Senior Big Data Engineer’s salary in India is ₹1,681,640 p.a. on average.
Average Salaries Across Different Cities
Here are the average salaries offered to these Big Data professionals in the different cities of India, according to Glassdoor:
Big Data Engineer salary in Bangalore: ₹897,000 p.a.
Big Data Engineer salary in Chennai: ₹1,171,000 p.a.
Big Data Engineer salary in Hyderabad: ₹946,000 p.a.
Big Data Engineer salary in Delhi: ₹820,000 p.a.
Big Data Engineer salary in Mumbai: ₹811,000 p.a.
The above numbers are directly impacted by several factors, including location, experience, skills, company, etc. Hope this blog gave you a clear idea of what kind of salary and income you can expect with a career as a Big Data Engineer in India. Consider the facts, and make the right career decision!
At Intellipaat, you can learn more about Big Data from our Big Data Community.