Data Engineer

Job Description

Job description

The data engineer, also known as Business Intelligence Developer, Datalogisticus, ETL Developer and Data Warehouse Developer, is a specialist in the technical design, development, integration and implementation of information assets such as Business Intelligence and Data Warehouse solutions. The realization takes place in both existing and newly built environments. Top Down, the data engineer analyzes information needs and system requirements as a basis for technical designs and knowledge models. Bottom Up, the data engineer analyzes information flows, processes, procedures and source data. After the analysis, the data engineer programs data flows that result in Data Lakes and Data Hubs for Data Discovery and integrated multidimensional data models for targeted data analyses. Customers are the intelligence analysts, data scientists and other information users in the organization.

About Us

Maximizing data utilization is what drives us

We believe in the value of data so much that we are prepared to commit ourselves to your success.

Job requirements

The data engineer is a forward-thinking person, who combines his IT, data logistics and data visualization skills with business affinity. The data engineer wants to use his skills in a ‘practice-driven’ big data setting, so that he or she can actually see the effects of his output. Although the data engineer likes to ‘immerse’ him or herself in large databases and data visualizations, he or she also enjoys investigating together with stakeholders how data can be used even more effectively and efficiently to create more value for the organization.

**Required technical skills**

• In-depth knowledge of Databases, Data Transformations and Data Visualizations;
• Knowledge of or experience with one or more programming languages ​​such as XQUERY, SPARQL, JAVASCRIPT, SQL, SAS Base and MDX;
• Knowledge of modeling data models such as Data Vault, Star Modeling, Third Normal Form Modeling, Triple Stores and Operational Data Hubs;
• Knowledge of Ontology Based Searching and Text Semantics;
• Knowledge of or experience with one or more software applications of SQL databases such as SQL Server, Oracle, Exasol, Snowflake and PostgresQL, of NoSQL databases such as MongoDB, MarkLogic and Apache Spark, of Hadoop Ecosystems such as Horton Works and Cloudera, of ETL tools such as Informatica, SSIS, BO Data Services, Data Bricks, Jitterbit, MuleSoft and Pentaho Data Integrator, of BI Front-end tools such as SAP Business Objects, Cognos, Birst, Microsoft PowerBI, Tableau, Yellowfin, Spotfire and SAS VA, of Modeling tools such as Powerdesigner, etc.