For this internship, we're looking for students who want to know more about data engineering and assist in developing state of the art best practices.
All data science starts with having data & getting this data, transforming it & making it available is the core responsibility of a data engineer.
Below, we have listed a number of topics which are relevant within the world of data engineering.
An end-to-end experiment with Image labelling & image recognition automation with Labelbox & Databricks
More & more organisations are looking into image recognition set-ups to speed up production monitoring, process control & process efficiency. To do this, images need labelling which is a recurring process of manual annotation, AI training & scoring.
In this internship, the student will work with the element61 team to set-up an innovative end-to-end set-up using Labelbox, Azure & Databricks to set-up image collection, image storage, labelling, AI training & scoring for a process/production manufacturing use-case.
Tools used will be at minimum Databricks (Python & Pyspark), Azure Data Lake, Labelbox and SQL.
- Using infrastructure-as-code & CICD principles to set-up an Analytics & AI Data Platform in minutes
element61 is already intensively using Terraform & CICD-ing using Azure Pipelines & Github Actions to automate data platform deployments. In this internship, the student will work with the element61 team to further automate & finetune this set-up making a thought-leading set-up of how automation in a data platform can drive data analytics use-cases. Tools used will be at minimum Terraform, Github Pipelines, Azure DevOps, Python, Bash and Azure Cloud
- Building a monitoring & alerting set-up for Data & AI pipelines
As organizations scale their data analytics & AI use-cases with many jobs running hourly & daily, companies need a solid set-up with proactive monitoring & alerting of data jobs succeeded, failed, logs & retries, etc. In this internship the student will start from the modern data platform architecture from element61 and work from there to propose, invent & build a solid set-up for best-practice monitoring & alerting. Tools used will be at minimum Python, Bash, Azure Cloud, Azure Data Factory and SQL.
This internship is about experimentation, research & learning. It’s about hands-on getting to know the data engineering space and extending the work of element61 and existing templates. The internship will include
- The learning part of enriching yourself with what is data engineering (something you don’t look at in school).
- The research part of how new framework can have an added value in our reference architectures, their pro’s & con’s.
- The technical part of actually setting up these new tool, trying them out & evaluating them hands-on.
As an intern, 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 & data engineering 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 firstname.lastname@example.org