Data Engineer

The main task of Data Engineers is to spot trends in data aggregations and build algorithms that are meant to transform rawly stored data into an output that is consumable within the organization. This role is highly technical and requires a strong knowledge of SQL and database architecture and mastering a set of other programming languages. However, Data Engineers typically have a quite developed understanding of business functions and can communicate effectively with business departments. A Data Engineer’s focus also encompasses the optimization of data accessibility and how data can be optimally visualized on top of other BI visualization tools. In some smaller companies, Data Engineers may be responsible to directly communicate insight to other stakeholders.

What are the main tasks of a Data Engineer:

  • Design, build and maintain data architectures.
  • Align database structures to business needs.
  • Acquire and optimize data streams into the data warehouse.
  • Come up with new ways to improve efficiency and quality of data across the organization.
  • Integrate advanced analytical applications, machine learning, and mathematical methods within existing processes.
  • Spot paths and unusual behavior within the data flow.
  • Implement automation of processes wherever possible across the organization.
  • Comfortably deal with large datasets to find solutions to business problems.

What are a Data Engineer’s requirements:

  • ETL tools development and maintenance.
  • Deep understanding of SQL and NoSQL databases.
  • Knowledge of data APIs.
  • Mastering of programming languages like Python, Java, Scala, R.
  • Understanding of algorithms and data infrastructures.
  • Strong mathematical and logical skills.
  • Good communication skills.
  • Understanding of how data processes fit into the business requirements.

To discover more about the role of Data Engineer in the current data roles spectrum please book a discovery call with us or visit our Data Engineer FAQ section.