Big Data has become quite a common term these days among professionals. As businesses are embracing data-driven strategies for meeting their goals, the demand for data engineers has increased all over the world. Evidently, professionals are taking up big data engineering training courses to explore their career opportunities in this emerging domain.
Data Engineering is basically associated with data – its delivery, storage, and processing. Data Engineers are responsible for providing reliable infrastructure for data. This article talks about what a data engineer is, his roles and responsibilities, and their salary prospects across the country.
What is a Data Engineer?
A Data Engineer works on data sets to find trends and develop algorithms so that the raw data may be converted into a useful format for an enterprise. They develop and translate computer algorithms into prototype code. They are accountable for maintaining, organizing and extracting trends in large data sets. Data Engineers usually need to work in teams.
To become a Data Engineer, a candidate needs to have a significant set of skills like a deep knowledge of SQL and Python, and preferred knowledge of Java or Scala. In addition to this, experience with cloud platforms like Amazon Web Services is desirable. A good understanding of SQL and NoSql(data modeling and data warehousing) is also required.
A Data Engineer has to be proficient in process documentation, and good verbal and written communication skills are also expected. The tasks like business metric aggregation and data management require a deep knowledge of programming languages like Java, Kafka, hive, storm and many more.
The tasks that a Data Engineer has to perform include aggregation and analysis of data sets to provide useful insights, developing dashboards, reports, and tools for business-professionals, finding out technical solutions for improvement of data access and usage, and understanding data needs and advising the company on technical resources.
The Data Engineer Role
Dataquest reports that there are three main roles that Data Engineers can perform, which are:
Generalist: every step of the data process, from managing to analyzing is done by generalists, who are usually meant to work in small teams, or companies.
Pipeline Centric: meant for mediocre companies, pipeline centric data engineers need “in-depth knowledge of distributed systems and computer science” as reported by Dataquest. They work parallelly with Data Scientists to utilize data that is collected.
Database-Centric: meant for larger organizations, the candidate is responsible for managing data-flow and focus on analytics databases.
Responsibilities of a Data Engineer
Along with managing and organizing data, while constantly checking for trends and inconsistencies that affect business goals. Besides having experience and skills in programming and computer science, a data engineer needs to have soft skills to communicate trends of data to other organizations. Some of the key responsibilities of a data engineer are:
• Data acquisition
• Align architecture with business requirements.
• Work to improve data reliability, efficiency, and quality.
• Develop data set processes.
• Develop, construct, test and maintain architectures.
• Prepare data for predictive and prescriptive modeling.
• Find hidden patterns using data.
These are some common responsibilities of a data engineer and may vary from company to company.
Popular Employers and Their Salaries
The Data Engineers find the best scope and salary in Amazon.com Inc with the payscale of around ₹1,400,000 annually. Other top respondents for the same are Tata Consultancy Services Limited and IBM Private Limited.
High salaries for this role are also offered by companies like General Electric Co (GE) that give around ₹1,017,500 annually and IBM India Private Limited offers a lower end of pay scale of ₹784,600. Tata Consultancy Services Limited pays the lowest amount of around ₹582,500.
Depending upon the skills, experience, and location, the salary of a Data Engineer ranges between $110,000 and $155,000 with an average of $137,770 per year, reported by Glassdoor. Here is a list of some of the top tech companies and the average salaries offered by them to their data engineers.
Top Skills for Data Engineer
The skills for Data Engineer that pay nicely are in-depth knowledge of Python, Apache Spark, SQL, ETL(Extract, Transform, Load), Apache Hadoop. Apache Spark pays you with the highest end of payscale of ₹993,068 and the lowest end of payscale comes with Apache Hadoop paying you ₹893,200. The skills may affect your salary negotiations by 10 or 15%, depending upon the skills.
Pay According to Experience
Obviously, there is a difference in salaries of entry-level data engineer and the one who has gained experience in the same. According to PayScale, an average salary of a data engineer at entry level may be ₹407,238 including bonuses, tips, and overtime pay.
A Data Engineer who has gained an experience of 1-4 years may expect an average salary of ₹739,916 based on 317 salaries. A data engineer at mid-career with an experience of 5-9 years may expect compensation of ₹1,227,921 based on 179 salaries. After gaining an experience of 10-19 years, a Data engineer can expect an average salary of ₹1,525,827 based on 49 salaries.
Pay According to Location
According to PayScale, a data engineer who works at Gurgaon, Haryana earns an average of 27.3% more than the average salary across the nation. Data engineers also earn more than the average salaries at Hyderabad(Andhra Pradesh,+13.7%), Bangalore(Karnataka, +12.5%) and Pune(Maharashtra). The cities where there is a lesser average salary are Mumbai, Maharashtra(18.8%less), New Delhi, Delhi(6.9% less) and Chennai, TamilNadu(6.6% less).
How to Become a Data Engineer?
Anyone with a bachelor’s degree in Computer Science, Engineering or applied Mathematics or a degree in a related IT field can become a Data Engineer. Aspiring Data Engineers may go for a certification course to boost their career because this field requires a deep knowledge of technology.
There are few certifications specific to data engineers like Cloudera Certified Professional: Data Engineer, Google Cloud Certified Professional Data Engineer, Certificate in Engineering Excellence Big Data Analytics Optimization(CPEE), IBM Certified Data Engineer-Big Data. Evidently, you are recommended to take up data engineering training programs and start a high-paying career in this domain.