Big Data EngineerJob Description, Salary, Career Path, and Trends
Big data engineers transform data into formats that can be easily analyzed, making data easily usable and accessible in multiple forms and for numerous departments. Big data engineers should have a robust knowledge of statistics, extensive programming experience — ideally in Python or Java — and the ability to design and implement solutions for big data challenges. Employers look for applicants with knowledge and expertise in data mining, processing large amounts of raw data, and developing and maintaining relational databases for storage and data acquisition.
Sample job description
Big data engineer needed at [Your Company Name]. As a big data engineer for [Your Company Name], it will be your duty to engineer data collection pipelines and manage the daily collection processes of our company. You must have experience with coding languages that are common in the big data collection field, as well as computer software, basic networking, and engineering. You will be responsible for the management and implementation of our systems, so you must be extremely confident in your ability to self-manage and produce results effectively. If you are a qualified candidate, you will have the required degrees and certifications for this position.
Typical duties and responsibilities
Develop and improve software systems
Design experiments to test system operations
Perform data mining to meet business objectives
Research, develop, and implement innovative techniques for the organization’s data
Work with large and complex sets of data
Education and experience
This position requires a bachelor’s degree in computer science, information technology, or applied math, preferably with certifications such as IBM Certified Data Engineer or Google’s Certified Professional. Many employers prefer candidates who have a master’s or doctorate.
Required skills and qualifications
Experience with object-oriented design, coding and testing patterns
Robust project management and organizational skills
Experience performing root cause analysis on internal and external data
Strong analytical skills related to unstructured datasets
Strong aptitude for business, technology, mathematics, and statistics
Expertise in written and verbal communication
Ability to work with a team to examine and solve complex issues
Proficient in computer programming and language
Experience with big data technologies
Technical data engineering experience
GCP Data Engineer certification
Experience in handling data security and governance
Experience in Google Cloud Platform
Average salary and compensation
The average salary for a big data engineer is $142,650 in the United States. Position salary will vary based on experience, education, company size, industry, and market.
Los Angeles, California
Minneapolis-St. Paul, Minnesota
New York City, New York
Typical work environment
A big data engineer is in charge of managing the data collection processes through a variety of fields. This engineer will be in charge of the development of the pipelines needed for data collection and similar duties. Big data engineers must have proficiency in a variety of fields and skills, including coding, computer software, and engineering. Because of this, a big data engineer may have a degree in a variety of fields and expand to the big data engineering field or have a more specified degree related to this job. As a big data engineer, you must have a competent understanding of NoSQL options, as well as big data knowledge and systems which are relevant to the position. Some of your common daily duties may include the implementation of new big data collection systems, the management and upkeep of existing systems, and the successful communication of data to systems managers.
The typical work hours for a big data engineer are from 9 AM to 5 PM, Monday through Friday, in an office setting.
A big data engineer is oftentimes required to have a certification or relevant certifications due to the nature of the position. Big data engineers may have a variety of degrees or certifications, but to ensure legitimacy some of the commonly recognized and widely accepted certifications include the following:
Cloudera Certified Professional. As a Cloudera certified professional, you will be industry-recognized and will receive training in pipeline engineering and production. Because of this, this certification can be immensely useful to a big data engineer.
Microsoft’s MCSE: Data Management and Analytics. If your position requires the use of Microsoft products or similar systems, then the Microsoft Data Management and Analytics certification can be immensely useful. This certification also helps demonstrate broad competency in SQL and similar database and big data systems.
The path to becoming a big data engineer begins with earning a bachelor’s degree in computer science, information technology, or applied math, preferably with certifications such as IBM Certified Data Engineer or Google’s Certified Professional. A candidate who goes on to receive a master’s degree may have expanded career opportunities. Most employers look for candidates who have relevant technical skills in high-tech tools and programming languages, including experience in Java, Spark, SQL, cloud programs like AWS, and UNIX.
US, Bureau of Labor Statistics’ job outlook
SOC Code: 15-1256
Projected Employment in 2030
Projected 2020-2030 Percentage Shift
Projected 2020-2030 Numeric Shift
According to industry website Computer Science Online, big data is now a significant component of the infrastructure, products, and services of organizations. Big data should be a $125 billion industry by the International Data Corporation, introducing a plethora of innovative processes, terms, and technology. This trend necessitates data management and interpretation skills, significantly increasing the demand for big data engineers.
Sample interview questions
Can you explain what big data engineering is and why it is so important?
How would you work with our engineering team to ensure success with our big data systems?
How would you go about optimizing models and algorithms in order to make them run faster?
What would you say your main responsibilities should be as a big data engineer?
If you are required to fix a faulty system, how would you go about troubleshooting and locating the issue?
Do you have any certifications in big data engineering?
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