Senior Data Engineer ( M/F/D )

Everience Benelux

Brussel Hoofdstad

Sur place

EUR 65 000 - 90 000

Plein temps

Il y a 30 heures
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Résumé du poste

Everience Benelux is seeking an experienced Data Engineer to join its collaborative Data & Digital team in Belgium. The role is hands-on, building data pipelines, improving data quality, and turning business needs into scalable data solutions using SQL Server, Azure Databricks and Data Factory.

You will work in an Agile product team, partner with Business Analysts and stakeholders, and continuously learn new tools.

Qualifications

  • 3–5+ years of hands-on data engineering experience.
  • Strong experience with SQL Server and Azure Databricks/Data Factory.
  • Python for data pipelines and data processing.
  • Master’s degree in CS, IT, Data Science or related field.
  • Strong analytical and problem-solving skills.
  • Ability to translate business needs into technical solutions.
  • Excellent communication with stakeholders.
  • Collaborative and product-oriented mindset.
  • Willingness to learn new technologies.
  • Fluent English plus French, Dutch, or German.

Responsabilités

  • Design, develop and maintain data pipelines and data processing solutions.
  • Work with SQL Server and Azure data services.
  • Build data solutions using Azure Databricks, Data Factory, Functions, Stream Analytics.
  • Develop data pipelines using Python in a Databricks environment.
  • Improve data quality, data modeling, data lineage and governance.
  • Collaborate with Business Analysts and stakeholders to translate needs into solutions.
  • Test solutions thoroughly and contribute to DevOps practices.
  • Keep documentation clear and up to date.

Connaissances

Fluent English
French/Dutch/German
Good communication
Collaborative mindset

Formation

Master's degree

Outils

SQL Server
Azure Databricks
Azure Data Factory
Python

Description du poste

Everience is an international consulting group delivering AI-augmented digital services and placing people at the heart of the AI revolution.

With a presence in Europe, Africa, Asia and America, Everience offers its 4,000-strong workforce the most demanding and stimulating environment in which to transform and develop their skills, learning about new AI-based roles and building their future employability.

Through its Symbiotic Academy the group offers a unique hub for training, practical application and exchange where everyone can experiment, learn, and progress in the fields of artificial intelligence and data.

In accordance with its core purpose of orchestrating the symbiotic relationship between humans and AI in the workplace, Everience is making the augmented employee the driving force of a “symbiotic age”, where AI enhances talents and opens up new career opportunities.

Job Description

We’re looking for an experienced Data Engineer to join a collaborative Data & Digital team and help build practical, reliable data solutions that have a real impact on the business.

You’ll be part of an Agile product team, working closely with other Data Engineers, Business Analysts and business stakeholders. Your role will be hands‑on: building data pipelines, improving data quality, working with different technologies and helping turn business needs into effective data solutions.

You’ll also have the opportunity to work with modern technologies and continuously learn and explore new tools.

What You’ll Do:
  • Design, develop and maintain data pipelines and data processing solutions.
  • Work with SQL Server and Azure data services.
  • Build and improve data solutions using technologies such as Azure Databricks, Azure Data Factory, Azure Functions, Azure Stream Analytics / Log Analytics and Azure DevOps.
  • Develop data pipelines and data enrichments using Python, particularly in a Databricks environment.
  • Help improve data quality and contribute to areas such as data modeling, data lineage, data glossary and data governance.
  • Work closely with Business Analysts and stakeholders to understand their needs and turn them into practical, reusable solutions.
  • Challenge requirements when needed and bring your own technical perspective to discussions.
  • Test your solutions thoroughly and contribute to good DevOps and development practices.
  • Keep documentation clear and up to date.
  • Share ideas, knowledge and best practices with your team.
  • Stay curious and be open to learning new technologies when needed.
Qualifications
  • 3-5+ years of hands‑on experience in Data Engineering or a similar role.
  • Strong experience in at least 2 of the following areas:
    • SQL Server
    • Azure services, particularly Azure Databricks and/or Azure Data Factory
    • Python for data pipelines and data processing
    • Data engineering and integration technologies
  • A good understanding of data pipelines, data processing and data quality.
  • A Master’s degree in Computer Science, Information Technology, Data Science, Engineering, or a related technical field.
  • Strong analytical and problem-solving skills.
  • The ability to understand business needs and translate them into technical solutions.
  • Good communication skills and the confidence to discuss requirements with both technical and non-technical stakeholders.
  • A collaborative mindset, you enjoy working with others, sharing ideas and helping the team succeed.
  • A product-oriented mindset, with a focus on creating solutions that bring real value rather than simply delivering technical solutions.
  • A willingness to learn and work with new technologies.
  • Fluent English & ( French or Dutch or German ) is mandatory
Additional Information

You’ll be joining a collaborative and Agile environment where you’ll have the freedom to bring your ideas, work closely with different teams and continuously improve the way things are done.

You’ll work on meaningful data projects, use modern technologies and have the opportunity to grow your technical expertise while staying close to the business.

All our positions are open to both women and men and are, of course, open to people with disabilities.

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