(Junior) Data Engineer/Scientist
At a glance
Junior Data Engineering role at Element61. Moore Brussel · full-time.
Pay not stated Data Engineer salary
dataroles summary, based on the employer's posting.
What you'll do
- Build data platforms and pipelines, then develop Python transformations and machine learning models
- Turn client use cases into platform designs and suitable machine learning approaches
- Advise client data teams on analytics, machine learning and generative AI challenges
- Bring Git, DevOps and CI/CD practices into client data platforms
- Coordinate delivery with client data specialists and business stakeholders against clear deadlines
What you bring
- A university degree in computer science or engineering, or a specialized master's in machine learning or AI
- Knowledge of machine learning methods and models, plus data science fundamentals such as sampling and evaluation metrics
- Fluency in SQL and Python
- You already live in Belgium
Who this fits
This junior role suits someone keen to learn across data engineering and data science through hands-on client projects. It combines platform and pipeline work with modeling, generative AI and customer guidance. You’ll work with client data teams and business stakeholders; no prior work experience is required.
From the employer
Data Science and Data Engineering go hand-in-hand, and a good Data Scientist has solid data engineering skills. During your first 18 months in this mixed Junior position, you'll get a rapid learning and hands-on curve working on the broad Analytics domains. You'll build Data Pipelines, set up Data Platforms, do CICD, build ML models, do feature engineering, do visualization exercises, and much more. This Junior position is a great opportunity to learn what it takes to do Analytics from end to end.
Our job offer is there to reflect a mixed Data Engineer/Scientist position: i.e., one where we’ll be asking you to crunch data with the objective to build data-driven insights, machine learning models, and to embed them in end-to-end applications (such as genAI applications) to production.
Key responsibilities
As a Data Engineer/Scientist, you aim to work hands-on to deliver data-driven platforms, machine learning models & genAI applications. Every mission we’ll embark on a trajectory with concrete deliverables and a deadline. This means that we can guarantee you a variety of engagements across clients & industries: e.g., one month you might be working on ingesting time-series data for a manufacturing customer and, another month, on a churn model for a marketing client.
- Build data platforms (data engineering) with Azure, Databricks, or Qlik
- Develop data pipelines & transformations and machine learning models in Python
- Guide customers towards translating their use case or business idea into platform architectures and machine learning techniques & models
- Act as a Data Science Expert on the latest machine learning & AI trends
- Be a thought partner for client Data teams in tackling their specific challenges, limitations & ambitions through machine learning, Data Analytics, and generative AI
- Inspire customers with insights and opportunities on new data-driven use cases
- Act as a Data Engineering Expert, bringing best practices of Git, DevOps & CICD to the customer's data platform
- Embrace project management aimed towards getting the job done. This will include working with client Data Scientists, Data Engineers, and also Business Stakeholders
- Be an on- and offline ambassador for the element61 team
Being a Data Engineer/Scientist at element61 means you will work with businesses and executives in Belgium, helping them to understand the impact of (big) data, analytics, machine learning & artificial intelligence. As time passes, we’ll encourage you to build a functional expertise within a business or technical domain within your interest, such as ad-tech, deep learning, digital marketing, predictive maintenance, or others.
- You are already residing in Belgium
- University degree in Computer Science or (Business) Engineering and/or a specialized master's in Machine Learning or AI, which reflects in
- Knowledge about machine learning approaches and the variety of models that exist & their application area (e.g., SVM, RNN, Deep learning)
- Knowledge about Data Science basics, including sampling and the various evaluation metrics
- Fluent in SQL and Python
- No working experience required; any experience can be a plus
- Knowledge of Spark and/or any Cloud ecosystem (Microsoft Azure, Google Cloud) is considered a plus
- First experience with generative AI technology is a plus
- Software development experience is a plus
- Passionate about data, machine learning technology & applications, and eager to learn
- Enthusiastic about being part of a growing team & industry
- Fluency in English, Dutch, or French is a plus
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