Where U Elevate Hiring Drive 2023 For Data Engineer | Location India  

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Where U Elevate Hiring Drive 2023:Where U Elevate Hiring for a job role of Data Engineer for India Location Jobseekers With 2-5 Years Of Experience candidates can apply for this job role ASAP.

Company Name:Where U Elevate

Role: Data Engineer

Location: India  

Experience: 2-5 Years

Qualification: Bachelor’s degree or better in Computer Science or equivalent

Batch: Any Batch

Salary: 7.2 LPA (Estimated)

Where U Elevate Hiring Drive

Key Responsibilities:

  • Reporting to the Data Integration Manager, the duties and responsibilities of the Data Engineer include, but are not limited to:
  • Model and architect data to solve business problems
  • Analyze and resolve technical and application problems
  • Create data pipelines to prepare and maintain data to solve specific use cases
  • Adhere to high-quality development principles while delivering solutions on time and on budget
  • Migrate existing workflows to newer infrastructures
  • Analyze use cases and propose solutions to meet business objectives

Dun & Bradstreet Hiring Drive 2023 For Data Engineer I| Location Hyderabad  

Job Skill:

  • Strong RDMS skills, utilizing MS-SQL or MySQL
  • Proven experience designing databases, troubleshooting performance issues, and writing advanced SQL queries and stored procedures for efficient data extraction and manipulation.
  • Experience building scalable and maintainable data-intensive applications
  • At least one modern programming language, preferably Python
  • Knowledge and experience with OOP design patterns
  • Pipeline orchestration technology, such as Prefect, Luigi or Airflow
  • Pipeline transformation tools, using Python and pandas library
  • Big data technologies, such as Hadoop & Spark, ideally including Python pandas and dask
  • Core Competencies
  • Keen interest in data engineering and a “tinkering” mindset
  • Driven to continually learn about and incorporate new technologies
  • Thrive in a self-driven environment
  • Understanding and integrating human and machine workflows
  • Data Lake & Warehouse Modeling
  • Git, Docker, Kubernetes
  • Cloud infrastructure, such as Azure, AWS, or Google Cloud
  • Development on Linux

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