Data Engineer

Permanent Sybrid Private Limited in Featured
  • Karachi/Islamabad View on Map
  • Post Date: June 16, 2020
  • Salary: PKRs50,000.00 - PKRs60,000.00 / Monthly
  • Applications 0
  • View(s) 1673
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Job Detail

  • Career Level Officer
  • Experience 0 - 2 Years
  • Gender Both
  • Qualifications Bachelors In Computer Science/Bachelors In Software Engineering

Job Description

Education: Bachelors In Computer Science/Bachelors in Software Engineering

Experience: 1 – 2 Years

Location: Karachi/Islamabad (Preferred Islamabad)

Job Description:

> Extracting Data from various Database and Data Ware House.

o   SQL required

>  Possess understanding of database management and in-depth knowledge of SQL and NoSQL databases such as SQL Server, PostgreSQL, DB2, MongoDB, etc.

> Loading Multiple csv or excel files or other structured/unstructured data into Database through single activity.

> Technical knowledge of data cleaning and transformation techniques.

> Hands on experience of using libraries of Python and R such as Numpy, Pandas, Scipy, dplyr, etc.

> Maintaining Database schemas and maintaining data pipelines and flow of data.

o   MS SSMS for interacting with SQL Server Databases

o   MS SSIS for Integrations services and Data pipelines

> Understanding of Networks for working with Databases in remote locations.

> Creating and maintaining various Data Architectures as per organizational requirements.

> Scripting to schedule Data Management Tasks on server.

> Ensuring that Data is up to date as per operational requirements.

o   If not, then the Data Engineer will be responsible for highlighting issue for inquiry.

> Technical knowledge of web scrapping and automation tools such as beautiful soup, scrappy, selenium, etc.

> Able to identify, design, implement and automate manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.

> Possess good knowledge of data structures, algorithms, operating system, distributed systems, machine learning, data warehousing, ETL and data integration.