Your role
As a Data Analyst or Data Scientist you trust that the data you have access to is correct, complete and of high quality. You want clean data for your analyses, reports & Machine Learning experiments. However many organizations struggle with Data Quality incl. missing data, missing values, changing column names, wrong master data, etc.
Great Expectations is a Python package to monitor data quality & set expectations smartly, allowing validating data as it enters through the Data & AI platform. Imagine having access to direct data quality statistics and/or alerts when data quality expectations aren’t met.
Your profile
Goal:
In this traineeship, the student will
- collaborate on embedding Great Expectations in a Databricks Lakehouse framework
- research & apply how to leverage it smartly and maximally for supporting Machine Learning & Analytics reporting use-cases with Databricks
This traineeship will combine both the technical perspective as well as the business perspective on how to quantify/measure & monitor data quality.
The student will be able to work with state-of-the-art technology while using this on a real-life use case.
As a trainee, we expect you to:
- Translate your academic knowledge into business solutions & a first hands-on experience;
- Do data development using Python, SQL in Azure and Databricks;
- Show your documentation and reporting skills through presentations and demo’s;
- Show creativity and out-of-the-box thinking in this challenging use-case.
What are we looking for:
- Character: customer-oriented, able to work in a team, keen to create something new in international teams;
- Working Practice: analytical, structured and result-orientated;
- Passionate about analytics, machine learning technology & applications and eager to learn;
- Enthusiasm to be part of a growing team & industry.
Language: working level English
Interested to find out more ? Send us your profile and motivation at jobs@element61.be