Data Engineer

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As a data engineer you are engaged in designing, inventing and developing technical solutions that make it possible to collect, store and subsequently analyze data. This data comes from internal and external offline and online sources and is used, for example, to map out strategies and make policy choices. 

There are different types of data:

  • Transaction data
  • Sensory data
  • Data from CRM systems
  • GPS data
  • Data from social media
A distinction is made between structured (unstructured) and unstructured (big) data. Structured data is quantitative data that is easy to process and can be stored in databases, for example place of residence or age. The majority of data that exists is unstructured. You can view this data as qualitative and - unlike structured data - cannot be captured in formats or figures. Examples of unstructured data are data from interactions on instagram. 
 
The duties of a data engineer include various activities such as:
  • Creating real-time reports / dashboards
  • Combining internal and external sources
  • Implementing machine learning models
  • Developing streaming and batch processes to collect data
  • Contributing to data landscape and cloud solutions and micro services such as AWS
  • Manage and optimize data flows and data warehouse
  • Designing infrastructure for big data lakes (storage of unstructured data flows)
  • Maintaining and optimizing the (cloud) infrastructure

A data engineer has knowledge of and experience with one or more of the following systems, tools and techniques:

  • Data processing processes: SQL (Structured Query Language) and ETL (Extract, Transform, Load)
  • Cloud computing: AWS and Azure
  • Programming languages: Python, Scala, Java, R
  • Data systems: Spark, Hadoop, MongoDB, Redis, Cassandra

Looking for a challenging data engineer position? Visser & Van Baars is happy to assist you in finding a suitable data engineer position!

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