Big data is now the hottest new IT trend with several opportunities. Companies are keen on hiring big data engineers. They work with databases and massive data processing systems in large-scale computing environments. They create and prepare companies’ big data tools, and infrastructure, and are the brains behind gathering data from various sources for data analysts and data scientists. Let us understand more about the key roles of a big data engineer.
Roles of a big data engineer
Big data engineers complete multiple tasks using skills drawn from different areas. They are responsible for the following:
- Working with IT teams and data architects on formulating project goals
- Developing highly scalable data management systems from the initial design phase to completion
- Designing prototypes, predictive models, and top-tier algorithms
- Developing applications including custom analytics
- Overseeing disaster recovery preparations
- Researching improvements to efficiency, reliability, and data quality
- Developing data set processes to be used for data production, mining, and modeling
Requirements to become a big data engineer
The path to seeking a career in big data engineering involves work experience, education, and optional certifications. Each step of the way, these engineers can sharpen their knowledge, and skills potentially boosting their chances of getting hired.
Students seeking a career in big data engineering should have an interest in math, statistics, computer science, or computer engineering. These subjects are introduced in high school and studied in-depth in postgraduate programs. At least a bachelor’s degree is required to enter the big data engineering field. It is recommended to have a master’s degree as it includes gaining software engineering expertise and advanced technical and analytical skills such as:
- Statistical analysis and modeling
- NoSQL databases, such as MongoDB and Cassandra
- Programming languages: Peri and Java, C/C++, R, and Python
- Business intelligence and analytics using cloud computing tools such as Azure and Microsoft BI
Software engineers or professionals seeking to grow their career in big data engineering must have at least two years of work experience in the related field. Students can gain work experience through internships and workshops even while earning their degree so that they develop the required competencies to become big data engineers such as analytical and communication skills, logical thinking, critical thinking, problem-solving, and attention to detail. For instance, IT professionals seeking to work or grow in big data engineering can hone additional skills to find creative solutions to several complex challenges.
Despite having the required degree and work experience cut-throat competition does not provide professionals with the right job opportunities in this field. Earning certifications is one such way to stand out from competitors and become appealing to recruiters. Big data engineering certifications are major international qualifications these days for programmers and software engineers aspiring to grow or even enter this field. The following are some reputed institutes that offer big data engineering certifications:
- Data Analyst Associate Certification by Microsoft
- Associate Big Data Engineer (ABDE) by the Data Science Council of America (DASCA)
- Google Cloud Certified Professional Data Engineer
- Cloudera Data Platform (CDP) Generalist Certification by Cloudera
A career in big data engineering may be perfect for professionals eager to grow in this lucrative field that aligns their passion for math, statistics, computer science, and more. Begin your journey towards becoming a big data engineer by earning the necessary skills and certifications that best suit your job role.