Big Data Engineer Salary and Career Trends in 2024

Download ebook

Big data engineers are the brains behind the sets of structured data that analysts and data scientists use. Architecture, technology standards, open-source alternatives and data management methods will all be part of the ecosystem in which this profession operates. There is indeed a huge demand for big data engineers. Big data engineer salary and career trends for 2024 are covered in this article.

The person in charge of developing and building data pipelines is a big data engineer. Big data engineers have years of expertise and significant technical understanding, and their jobs are in high demand. A Bachelor’s degree in computer science, software engineering, mathematics, or another IT field is required if you want to work as a big data engineer. In addition to a degree, a big data engineer needs a range of technical skills to be successful in their role. A prospective big data engineer can therefore succeed with the correct expertise in SQL, Python, and several cloud platforms.

Big Data Engineer Salary in India

Top Needed Skills for Data Engineers:

Big Data Engineer Salary Offer in Companies

Salaries by the company according to the experiences.	Salary Estimation
TCS – Big Data Engineer Salary (1-6 exp)	₹ 5.9L
IBM- Big Data Engineer Salary (2-9 exp)	₹ 12.1L
Accenture- Big Data Engineer Salary (1-6 exp)	₹ 8.3L
L&T Infotech- Big Data Engineer Salary (1-6 exp)	₹ 7.0L
Cognizant – Big Data Engineer Salary (1-7 exp)	₹ 7.6L
Capgemini – Big Data Engineer Salary (1-6 exp)	₹ 7.2L
Wipro – Big Data Engineer Salary (1-7 exp)	₹ 7.3L
Fractal Analytics – Big Data Engineer Salary (2-5 exp)	₹ 13.7L
EC-Mobility – Big Data Engineer Salary (1-4 exp)	₹ 2.2L
Infosys – Big Data Engineer Salary (1-5 exp)	₹ 5.8L

Bangalore is the location of many of the nation’s data engineering employment, and employers like Amazon, IBM, and Autodesk typically fill these positions.

Big Data Engineer Salary in Other Regions

• The average pay for a data engineer in Australia is AU$98,753 per year, according to PayScale.
• According to PayScale, average annual compensation for a data engineer in Canada is C$80,610.
• The average annual compensation for a data engineer in Singapore is S$61,688, according to Pay scale.
• According to Salary Expert, average annual pay for a big data engineer in Mexico is MX$ 483,598.
• The average annual income for a data engineer in South Africa, according to Indeed, is R 544,145.
• According to Glassdoor, average annual wage for a data engineer in Spain is €35,439.
• The average pay for a data engineer in Germany is € 62,145 per year, according to Glassdoor.
• According to PayScale, average annual wage for a data engineer in Sweden is 457,645 kr.
• The average pay for a Data Engineer, per LinkedIn in France is €42,500/year.

Big Data Engineer’s Annual Salary in The UK.

Data engineers in the UK make an average yearly pay of £48,481. There are several businesses actively seeking data engineers in locations like Liverpool and London, and Shop Direct and Tessian are just two examples.

Salary for a Big Data Engineer in Toronto, Canada

Data engineers in Toronto have an average annual salary of CA $88K. Among the organizations in the city seeking candidates for data engineering opportunities are Scotiabank and IBM.

Big Data Engineer’s Annual Salary in the US.

The compensation range for a big data engineer in the US is from $68,931 to $155,000, with a median pay of $90,000. The average yearly salary for big data engineers is between $90,000 and $110,000, and 86% of them make over $155,000.

Yet, as mentioned below, this figure can differ greatly by state and even by city.

NYC: $118,168 is the average yearly salary in New York. With large companies and brands like CapitalOne, there is often always a great demand for big data specialists.

Los Angeles: With data engineers making an average of $114,138 per year, Los Angeles is only slightly behind New York City. Target, Hulu, and GumGum are just a handful of the companies looking to hire data engineers right now.

Seattle: Data engineers in Seattle make, on average, $120,903 a year. Many companies, like Amazon and Microsoft, are now hiring data engineers.

A Career Opportunity in Big Data

Data Analyst

An organization’s data systems are examined by a data analyst, who also works to improve the systems. They assist the data scientist in gathering the necessary data and are in charge of gathering data from various sources to aid in the analytics procedures. The necessary reports must also be produced by data analysts. It is one of the good careers in big data.

Analyst of Data

Large amounts of data must be analyzed by a data scientist to produce insights that assist the company in making decisions. To evaluate the data and derive insights, they make use of machine learning, statistics, and a variety of technologies. It is one of the good careers in big data. The investors and higher management are among the stakeholders with whom data scientists share their thoughts.

Engineer for Data

To achieve the objectives of data science and business, a data engineer handles the data starting with the raw source and makes sure that it is processed, stored, and accessible in the needed format. Data engineers are leaders who manage vast amounts of unstructured data and make sure that their organization’s big data initiatives align with its objectives and needs. It is one of the good careers in big data. They must also assess fresh conventional and non-conventional data sources.

Data Architect

A data architect is a professional who aids in the planning and construction of the necessary big data architecture for their firm. To properly build big data platforms, they must be aware of the requirements of their firm. It is one of the good careers in big data.  To create data workflows and test the many prototypes, data architects collaborate with other big data experts.

Current Job Trends in Big Data

Compared to many other tech industries, big data occupations pay a lot more. Big data analytics professionals make an average of INR 12.8 lakh annually. Remember that both junior and senior roles are represented in this number. Businesses only offer such high rates for abilities when there is a dearth of qualified candidates. Since it is a good career in big data. They are actively searching for candidates who can fulfil the needs of big data jobs.

The need for big data positions has also increased as a result of the nation’s growing number of startups. Startups innovate and disrupt the market, and they depend on talented people to help them succeed. Since big data specialists are among the most technologically advanced in any industry, they draw interest from a variety of industries.

A Career in Big Data Benefits

Choosing a career in big data has several benefits. Here are a few advantages:

A High-Demand Industry

There is a constant need for big data specialists. Also, there is a growing need for such knowledge, so there is no need to worry about job security when you enter this profession. You can more easily plan your career and have more possibilities when looking for a big data job if you join a growing business.

Employing Reputable Brands

Industry specialities for big data experts include technology, management consulting, healthcare, and finance. You will have the chance to work with some of the most well-known companies in the world, such as Adobe, Google, Microsoft…etc.

Generous pay

In a career in big data, in India, the average yearly salary for a data engineer is 8.37 lakh rupees. Depending on your expertise and abilities, you might earn up to INR 20 lakh per year in this position. The fields of data scientist, business analyst, and data architect are only a few examples of those in comparable big data. The remuneration for big data jobs is undoubtedly quite high.

What is Big Data?

Massive amounts of consumer, product, and operational data—often in the terabyte and petabyte ranges—are referred to as “big data.” Big data analytics can be utilized to reduce compliance and regulatory risks, increase new revenue sources, and optimize important business and operational use cases.

Among the data sources are credit card and point-of-sale transactions, online purchases, social media interactions, mobile device and smartphone usage, and internet of things sensor data are all examples of transactions (IoT).

Big data can provide insights on things like enhancing important business and operational use cases, reducing compliance and regulatory risks, generating new sources of income, and developing engaging, distinctive consumer experiences.

What Does a Big Data Engineer Do?

A big data engineer’s responsibility is to create, maintain, and guarantee a big data environment that is suitable for production. The context in which this function operates will comprise architecture, technological norms, open-source choices, as well as procedures for data management and data preparation.

The function of a big data engineer is to:

• Develop, build, and maintain systems for processing huge amounts of data. This compiles data from several sources, both structured and unstructured.
• A data lake or warehouse should be used to store data.
• Use data processing transformations and algorithms to handle raw data to produce present data structures. Add the results to a data lake or warehouse for processing later.
• A scalable data store should be created by transforming and combining various data (such as a data warehouse, data lake, or cloud).
• Know the various techniques, plans, and algorithms applied to data transformation.
• Employ business logic and technology processes to transform gathered data into insightful and useful information. This data must meet the standards for quality, governance, and compliance to be trusted for operational and business use.
• Understand the variations among hybrid clouds, massively parallel processing (MPP) databases, and data repository architectures, as well as the operational and administrative choices.
• Data pipelines should be analysed, compared, and improved. Examples of this include the development of design patterns, data structure design, data ontology alignment, annotation data sources, and elastic search approaches.
• Create automated data pipelines to change the data and feed it into the development, quality control, and production environments.

What Are The Duties And Talents of a Big Data Engineer?

Big data gathers, processes, and ingests data from an organization into a big data environment. They set up and build data pipelines and extraction processes that automate the collection of data from numerous internal and external source sources. The methods used to convert the data into an operational or business format are also developed by big data engineers.

Understanding the following is necessary to land a position as a successful big data engineer:

1. Examples of typical data archetypes include algorithms, the development of logic, control flow, object-oriented programming, working with external libraries, and compiling data from various sources. Knowing databases, scraping, APIs, and publicly available repositories are all part of this.
2. Structured data sources include RDBMS and spreadsheets, semistructured sources include log files, XML, and JSON, and unstructured sources include everything else (like text, video, audio, and image files).
3. Relational databases and NoSQL databases (using dimensional modelling, entity-relationship diagrams, and SQL) (such as Hadoop, Spark, and massively parallel processing databases).
4. SQL-based database queries that make use of joins, aggregations, and subqueries.
5. Applications for real-time data processing such as Beam, Kafka, and Spark Streaming, time series databases such as InfluxDB, relational databases such as Postgres and Neo4j, and development platforms such as Git and GitHub are examples of open-source tools.
6. Tools for an abstraction like Kubernetes.
7. Mastery of C, C++, Java, and Python programming and scripting languages. Having the ability to create programming and processing logic as well.
8. Knowing automated machine learning (AutoML) and machine learning techniques to automate and construct pipelines for continually learning data processing.

How to Become Big Data Engineering – Road Map.

Most people go through several steps on their path to creating a career as big data engineers.

Degree

All of the aforementioned technical abilities must be mastered to become a big data engineer, which requires extensive study. Big data engineers frequently hold bachelor’s and master’s degrees in a closely related field, including business data analytics, statistics or computer science.

For big data engineers, coding, analytics, and data understanding are necessary. A bachelor’s degree is typically required for big data engineer employment in businesses.

Experience

Experience is a must for becoming a big data engineer. You can get experience through freelancing, internships, independent practice, or employment in related fields. With experience, your prospects of finding work as a big data engineer improve.

Certificates

Acquiring professional certifications can also be quite helpful for landing a job as a big data engineer.

Henry Harvin’s Course on Big Data Analytics

Rating 9.9/10

The Big Data introduction is covered in this course. A survey of the Hadoop and Spark frameworks, which offer notable tools to manage a vast amount of data, is provided in the Big Data Analytics course. The tools and technologies used in big data ecosystems, including YARN, HDFS, MapReduce, Hive, and others, will grow even further thanks to this course.

9 lessons in one Course.

• 32 hours of interactive, live online instruction.
• The internship was offered so that students may learn more about big data analytics.
• the availability of projects in areas like Big Data SQL, Spark, Kafka, and many others.
• The Henry Harvin Institute, a prestigious institution with the government of India recognition, offers the Certified Big Data Analyst(CBDA) credential.
• 100% placement is ensured after one year of successful completion.
• E-learning includes video content, tests, a variety of practice tools and methods, and more.
• Regular boot camps over the following 12 months.
• Free entry to competitions and hackathons.
• Obtain Henry Harvin’s Gold Membership for a year.

Advantages of learning.

• Become well-versed in the Hadoop Framework.
• Use HDFS and YARN for Hadoop.
• learn a great deal about MapReduce.
• Gain knowledge on the fundamentals of Hive illustration and loading different file formats.
• Learn how to pack data into Hive tables and work with external tables in the database.
• Query operations can be performed on Hive tables.
• Recognize Apache Kafka as a platform for distributed streaming.
• Spark configuration and performance modulation management. serialization of data.

Career Advantages.

• Get qualified for challenging jobs like Big Data Analyst.
• Fill the talent vacuum for thousands of high-paying jobs in big data analyst businesses.
• Make deliberate, well-thought-out decisions for a Big Data Framework as an individual.
• Describe all Big Data Analytics Framework functionalities in a business model.
• When you go to job interviews, set yourself out from the competition.
• Get the lucrative Certified Big Data Analyst Credential.
• With a certification in big data analysis, you can play a vital role in the business.
• Develop and enhance your LinkedIn profile and resume on a professional level.

Course Outline

• Hadoop: Be an expert in large data.
• Huge data: Hive Streaming and analysing massive data using SQL Spark.
• A distributed streaming platform is Apache Kafka.
• Advanced spark.
• Complementary Module 1: Developing Soft Skills
• Complementary Module 2: Creating a resume.

Contact Detail: +91 9891953953

Recommended Blogs

• Scope of Big Data Analytics Courses in 2023.
• Types Of Jobs In Data Science in 2023 [Updated].
• 30 Best Institute for Data Science Courses in Chennai with Fees & Duration 2023 Updated.

Conclusion

This is the ideal time to pursue a big data profession. Companies are aggressively searching for big data specialists since there is a dearth of qualified big data workers. Throughout the upcoming years, it is predicted that the big data industry’s market size would significantly grow. The need for big data specialists will increase along with it.

FAQ

Download ebook