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IT Data Engineer / Security Engineer

4.00 to 7.00 Years   Kuwait   16 Dec, 2024
Seazen Group
100 to 499 Jobs Openings
Job LocationKuwait
EducationNot Mentioned
SalaryNot Mentioned
IndustryCatering, Food Service, & Restaurant
Functional AreaNot Mentioned

Job Description

The main objective of this position is to develope, maintaine , and test infrastructures for data generation with Development team .He / She will be largely in charge of architecting solutions for Data transforming data , into a format that can be easily analyzed by differents departments. Key Responsibilities

  • Create and maintain optimal data pipeline architecture based on SeaZen Core System Integrations
  • Assemble large, complex data sets that meet functional / non-functional business requirements.
  • Responsible on building and architecting the DWH on AZURE alongside with Developments team
  • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
  • Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AZURE ?big data? technologies.
  • Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
  • Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
  • Keep our data separated and secure across national boundaries through multiple data centers .
  • Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
  • Work with data and analytics experts to strive for greater functionality in our data systems.
  • Reformulating existing frameworks to optimize their functioning.
  • Preparing raw data for manipulation by data scientists.
  • Ensuring that your work remains backed up and readily accessible to relevant coworkers.
  • Remaining up-to-date with industry standards and technological advancements that will improve the quality of your outputs.

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