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Frequently Asked Questions:

• How many Data Engineer jobs are available on Pertemps?

  There are 88 Data Engineer jobs available on Pertemps right now.

• What does a Data Engineer do?

  A Data Engineer is a professional responsible for designing, building, and maintaining the architecture of data systems. They work with large volumes of data and are involved in tasks such as data modelling, ETL (Extract, Transform, Load) processes, data warehousing, and database management.

  Tasks required include:

  • Design and create data models that define the structure and relationships within datasets, ensuring efficient storage and retrieval of information..
  • Design, implement, and manage databases that store and organize structured and unstructured data..
  • Develop and implement ETL processes to extract data from various sources, transform it into a usable format, and load it into data warehouses or other storage systems..
  • Integrate data from different sources and formats, ensuring consistency, accuracy, and compatibility..
  • Design and maintain data warehouse architectures to support business intelligence, reporting, and analytics requirements..
  • Work with big data technologies such as Hadoop, Spark, and NoSQL databases to process and analyse large datasets..
  • Create and optimize data pipelines for the efficient flow of data between systems, applications, and databases..
  • Implement data governance practices and policies to ensure data quality, security, and compliance with regulatory requirements..
  • Optimize database and query performance to ensure efficient and fast data retrieval..
  • Implement security measures to protect sensitive data, including encryption, access controls, and data masking..
  • Monitor data systems for performance issues, errors, and bottlenecks, and perform regular maintenance activities..
  • Design data architectures that can scale to handle growing volumes of data and increased demand..
  • Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and provide the necessary infrastructure..
  • Use version control systems to manage changes to database schemas, ETL processes, and other components of data systems..
  • Maintain comprehensive documentation of data architectures, processes, and configurations..
  • Implement automation for repetitive tasks, improving efficiency and reducing manual errors..
  • Implement processes and checks to ensure data quality and accuracy throughout the data lifecycle..
  • Stay abreast of emerging trends and technologies in the field of data engineering..

• What are the entry requirements for a Data Engineer?

  There are no formal academic requirements, although entrants typically possess GCSEs/S grades or an equivalent qualification. Apprenticeships and traineeships combining work experience and practical training are available at NVQ/SVQ Levels 2 and 3.