Azure Data Engineer

  • Full Time
  • Rainham
  • Salary Guide: £30,000 - £65,000

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Hatigen Consulting Services Limited

Hatigen Consulting Services is a growing organisation and we not only aim to persevere as an organisation, but also, our objectives and goals are desi... Role: Data Engineer, Category: IT & Telecoms, Size: N/A

Azure Data Engineer: Hatigen Consulting Services Limited

Hatigen Consulting Services is a growing organisation and we not only aim to persevere as an organisation, but also, our objectives and goals are designed in a way where every member of the Hatigen family has a learning curve in their specialisations. We keep updating and enhancing our processes and bring out the best in the market for you to expand your thoughts and skills and provide opportunities to learn, expand and work extensively on new technologies that have been proven to be dominating the tech world. We at Hatigen are driven to find a solution that fits your challenge.

Position: Azure Data Engineer
Location: Rainham
Hours: Full Time
Salary Guide: £30,000 – £65,000
Last Updated: 15 June 2022
Job Category: IT & Telecoms

Data Engineer Role:

Analyze and organize raw data . Build data systems and pipelines. Evaluate business needs and objectives. Interpret trends and patterns. Conduct complex data analysis and report on results . Prepare data for prescriptive and predictive modeling. Build algorithms and prototypes. Combine raw information from different sources. Explore ways to enhance data quality and reliability. Identify opportunities for data acquisition. Develop analytical tools and programs. Collaborate with data scientists and architects on several projects.

Other Duties:

  • Analyze and organize raw data
  • Build data systems and pipelines
  • Evaluate business needs and objectives
  • Interpret trends and patterns
  • Conduct complex data analysis and report on results
  • Prepare data for prescriptive and predictive modeling
  • Build algorithms and prototypes
  • Combine raw information from different sources
  • Explore ways to enhance data quality and reliability
  • Identify opportunities for data acquisition
  • Develop analytical tools and programs
  • Collaborate with data scientists and architects on several projects



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