Data Engineering Roadmap 2023: Data engineering is a fascinating and rewarding job since you are at the helm of every company process that uses data, and organizations will always need data engineers as long as users provide data. To put it another way, job stability is guaranteed.
However, tremendous power comes with great responsibility. The path to being a good data engineer is treacherous terrain that you must travel and master from the outset. In this brief and to-the-point post, I’ll lead you through the full process of becoming a data engineer, avoiding typical traps along the way.
Data engineer roadmap
Data Engineering is the process of developing feasible designs for large-scale data extraction, storage, and inspection systems. It entails creating pipelines that can retrieve data from a source, change it into a usable format, and analyze variables in the data. These pipelines provide hidden facts about a company’s overall operation and assist stakeholders in understanding their clients, outreach, sales, and so on.
The company needs a data engineer
Gartner forecasted in 2021 that 85% of data-driven programs would fail while delivering the anticipated objectives. However, with firms rapidly increasing their spending on data infrastructure, the prognosis is likely to be incorrect. In addition, organizations are likely to recruit professionals that can assist them in efficiently using data. That is why company managers need data engineers, since they will engage with raw data, clean it, polish it, and make it analysis-ready.
Data Engineer Roadmap Future
Since 2016, there has been a significant increase in the need for data engineers. Years later, we see a lack of competent data engineers and a rise in the number of employment. According to a DICE analysis from 2021, data engineer is the fastest-growing career role, with a 50% annual growth rate in 2022.
Data Engineer Roadmap Responsibilities
- Convert erroneous data into a usable form for further analysis.
- Create large data warehouses using ETL.
- Develop, test, and maintain architectures.
- Develop dataset processes.
- Data Engineer Roadmap Eligibility Criteria
- Graduate-level mathematical proficiency.
Data Engineer Roadmap Eligibility
- Excellent command of computer programming languages such as R, Python, Java, C++, and others.
- Advanced probability and statistics require a high level of efficiency.
- Expertise with database management systems is required.
- Experience with cloud service platforms such as AWS, GCP, and Azure.
- A good understanding of different machine learning and deep learning methods will be advantageous.
- Understanding of major big data tools such as Apache Spark, Apache Hadoop, and others.
- As a data engineer, you must be able to communicate effectively because you will be working directly with several teams.