Introduction

Since the last ten years have seen such rapid growth in big data, the required skills have become more specialized. Although Hadoop is the foundation in most cases, several tools have become quite significant. Data creation and consumption today seem to have no end. The critical question is how this information will be kept, protected, processed, and visualized. A prominent data engineer develops the approaches and strategies to handle these difficulties. Even though large data is still just data, it needs to be engineered differently for various reasons. Big data is a vast collection of unstructured, messy information constantly proliferating. Therefore, conventional data transportation methods could be more effective in managing.

The main emphasis will be on selecting the best solutions for these reasons, then keeping them up to date, putting them into practice, and monitoring them. Additionally, you will be in charge of connecting them with the corporate architecture.

Responsibilities and Job Requirements

• Choosing and integrating any Big Data frameworks and tools necessary to deliver the needed capabilities
• putting data in place through the ETL method
• Keeping an eye on performance and suggesting any necessary changes to the infrastructure
• Creating data retention guidelines.
• Create and deploy pipelines that help the organization achieve its strategic goals by extracting, transforming, and loading data.
• Put your attention toward acquiring, storing, processing, and analyzing massive datasets.
• Create scalable, quick web services for data tracking.
• Convert intricate technical and functional specifications into detailed designs.
• Look into several data handling and storage options to ensure the most efficient solutions are used.
• Tutor less experienced staff members by leading technical training sessions and examining project outcomes.

Education and Experience

• Create and deploy pipelines that help the organization achieve its strategic goals by extracting, transforming, and loading data.
• Knowledge of Spark, Hive, and Python.
• Knowledge of data modeling and warehousing approaches and understanding of common visualization and analytics tools.
• With the Azure cloud platform, strong data engineering capabilities are needed.
• Knowledge of streaming frameworks like Kafka.
• Knowledge of any scripting language, Linux, SQL, and core Java.
• Must have Strong interpersonal abilities and a cheerful outlook.
• Degree in engineering, mathematics, or computer science; proficiency with ETL technique for designing corporate-wide solutions using DataStage.

Work hours and Benefits

The job is for full-time employees in which the number of hours can depend on company working policies. The estimated salary one can earn is up to $133K per year. The salary can be increased as the experience is improved. Some jobs also offer hour-based contracts in which one can expect 70$+ for an hour. The MNC provides suitable employee facilities, including some education credits, a free work laptop, and some perks.

Action

Consider that the job description appears relevant and that all requirements match your skill sets. In that situation, applicants can apply for the company’s official email address on the corporate website. The person must finish the required steps after passing the profile selection round. Your age, religion, country, gender, and color won’t be considered during the procedure.