Data · Role
Data Engineer
A data engineer builds and maintains the systems that collect, store, and move data within an organisation. Without this infrastructure, analysts and data scientists have no reliable data to work with.
In this role you might set up a data pipeline, fix a broken data flow, or work with a data analyst to make a new data source available.
The goal of a data engineer is to make sure that data gets from its source to the people and systems that need it, reliably and on time. If that infrastructure breaks, reporting stops and analyses become unreliable.
Most of the daily work involves building and maintaining data pipelines. A pipeline is a process that automatically moves data from one place to another, for example from a sales system into a central database. You also monitor existing pipelines, fix errors, and make sure data is stored in a clean and consistent format.
The main tools are SQL, Python, and cloud platforms like AWS, Google Cloud, or Azure. Tools like Apache Spark or dbt are common for processing large amounts of data. Data engineers also work with orchestration tools like Airflow to schedule and monitor pipelines.
The role sits close to software engineering. The work is more technical and less focused on analysis than a Data Analyst role. At larger companies, data engineers work in dedicated teams. At smaller companies, the role often overlaps with data analysis or software development. In the Netherlands, financial institutions, tech companies, and large retailers all employ data engineers. The role connects closely to Data Analyst and Data Scientist roles, which depend on the infrastructure a data engineer provides.
Related sectors
Sectors where Data Engineer roles are most common.
Projects
Projects relevant to Data Engineer, grouped by problem type.
Companies
Organisations where graduates typically work as Data Engineer.
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Note: this list is an approximation. An organisation's actual work, roles, and terminology can differ from the categories shown here.