Big Data Engineer Jobs

Big Data Engineering is a new and emerging field of Data Science. Based on a recent analysis by MarketsandMarkets, this sector is predicted to grow at a Compound Annual Growth Rate (CAGR) of 12.7% from 2023 to a startling USD 401.2 billion by 2028.

The Big Data Engineering market is booming, and Tutorials Point is here to bridge the gap between aspiring big data professionals and their dream jobs! Our 360 learning platform equips job-seekers with the skills they need to thrive in this lucrative sector.

What Does a Big Data Engineer Do?

Big data simply means huge sets of complex data. Businesses generate enormous volumes of data in today's data-driven environment, from financial transactions to consumer interactions. But, to realize its full potential, businesses want experts, i.e. big data engineers. Big data engineers work on these large datasets to build, maintain, test, quantify, extract, and analyze a company’s data.

Big data can become a liability to the company if not managed appropriately. Inadequate or inaccurate data may restrict the expansion of businesses and even result in poor decision-making. Therefore, for businesses, the role of Big Data Engineers is essential to provide consumers with data that is clean, dependable, useful, and of excellent quality. This structured and organized data can be used in multiple ways to produce quicker, more precise commercial insights.

Career Score of Big Data Engineers

Because of the widespread digital revolution of businesses, the reach is broad and expanding. Big Data Engineers are in high demand in the IT, e-commerce, financial, and healthcare industries for their ability to handle, interpret, and examine massive data volumes.

The massive amount of data today is making businesses all over the world rely on Big Data. Big Data technologies and tools help them handle all this information, make better decisions, and expand the job opportunities for big data engineers.

According to a Flexera report, a whopping 94% of businesses have adopted cloud technologies, highlighting the ever-increasing cloud usage across various industries. Data engineers are playing a leading role in this cloud migration.

Data discrepancies can result in substantial financial losses for organizations as huge as an average annual cost of $15 million per organization. This is where Big Data Engineers come into play.

A recent study by KDnuggets highlights the growing significance of cloud platforms offered by companies like AWS, Azure, and GCP. This trend is in accordance with the rising importance of frameworks such as Apache Kafka and Spark Streaming, that handle data in real-time.

Average Salary of Big Data Engineers in India

Based on Experience
Entry-level (Below 3 years): ₹7.3 LPA.
Mid-Level (4-9 years): ₹12.9 LPA
Senior-level (10-20 years): ₹23.7 LPA
Source: AmbitionBox

Average Salary of Big Data Engineers in Different Countries
United States: $1,29,102 per year
United Kingdom: £52,383 per year
Canada: CA$1,06,407 per year
Australia: A$1,19,600 per year

Top Companies That Hire Big Data Engineers

Apart from the big 4, companies that manage large databases frequently hire Big Data Engineers:

IBM
Uber
Amazon
Google
Sprint
OpenAI
Netflix
LinkedIn
Mindtree
WalmartLabs

Big Data Engineers Responsibilities

• Big Data Engineers are quickly becoming a crucial segment of the Data Science field, playing a vital role in unlocking the power of information for organizations.
• Build high-speed data processing systems that can handle a variety of data formats for efficient analysis.
• Use Big Data technologies, including Hadoop, Spark, and Cassandra, to handle and process massive datasets efficiently.
• Ensure that data is transformed, organized, and integrated from various sources. This allows for seamless upload to a powerful cloud storage system..
• Troubleshooting performance issues in data processing pipelines and algorithms through the identification of blockages.
• Investigate new data acquisition strategies and conduct research to identify unexplored applications for established data sets.
• Maintain custom systems to connect data sources, store them effectively, and further analyze them for better insights.

Top Skills Required to Become a Big Data Engineer

• Data Mining
• Data Modelling
• Data Architecture
• Data Acquisition
• SQL and NoSQL
• Data Warehousing and ETL Tools
• AI-ML
• Hadoop
• DevOps
• Apache Spark
• Apache Kafka
• Programming languages like Python, Java, C++

How to Become a Big Data Engineer

Big data engineering is a multifaceted field. So, to become a big data engineer, you need to be proficient in multiple skills that involve not just coding, but critical thinking skills and hands-on experience with data engineering tools like Hadoop, Spark, and Kafka. To kickstart your career in this exciting and dynamic field,  follow the below-mentioned steps:

Get a Relevant Degree: Aspiring big data engineers require a bachelor's degree in a computer-related such as computer science, software engineering, or any other specialization. Alternatively, a relevant IT degree may also work. Most big companies require a Bachelor’s or Master’s degree with a specialization in Big Data for related positions.

Internship and Training: full-time work experience in the field will surely give you the edge, but if you are just starting your career, taking up an internship or training will be beneficial in landing a high-paying job in a good company. It will also equip you with industry-relevant skills for the marketplace.

Upskill with a Certification: Earning a degree is not enough. There are multiple skills that a Big Data Engineer is expected to be skilled at, to land a high-paying job. The good news is that these skills can be mastered by enrolling in a good certification program. TutorialsPoint Data Science Certification 2024 (insert link here) provides project-based learning and covers everything that a Big Data learner requires from basic to advanced levels. From data visualization to R programming to Deep Learning, work on real-world case studies in this step-by-step course series.

Build a Resume: Building a compelling resume is the first actionable step toward making a career in big data engineering. Your resume acts as a medium to showcase your skills and a chance to impress the recruiter with your expertise before the actual interview. If you are a fresher, include freelance work, internships, certifications, and training. If you are experienced, mention your roles and responsibilities as a big data engineer and how you contributed to your firm.

Prepare for Interview: Interview preparation is the final step to begin the journey as a Big Data Engineer. If you are a fresher, ensure you have a strong hold on the technical concepts and your basics are clear. You can refer to Glassdoor and Ambitionbox for reference interview QnAs for the organization you interview for.

Apply through the Right Platform: The final step is to select a valid job portal to apply for jobs. Use the TutorialsPoint Search Job Page to apply for the latest jobs in the domain from all over the world. Browse among positions for entry-level, remote, and fresh graduates. Examine the job descriptions for big data engineer positions, then apply to the roles that interest you