Schuberg Philis continues to expand its focus on data for growth, which means that we are looking for Data Engineers. We keep our customers moving forward by designing, building and running their data landscapes. These landscapes are often developed in public cloud environments, but there is diversity in implementation: not all customers are the same and neither is our internal organization. We have data lake environments on our own MCC (Mission Critical Cloud), AWS, Azure, and more.
As a data engineer, you will:
- Develop and maintain data pipelines
- Manage our data lake for reporting purposes
- Build collectors (Lambda, DMS, Spark or Glue) and processes in Airflow
- Configure and manage tools like Cloudformation (CDK)
- Use support tooling such as Gitlab (CI/CD)
- Focus on the technical implementation of use cases and required tools on a new data platform
- Be involved in the data standards and initiatives that we have set for our customers
In this role, you have the autonomy to, together with your team, decide how to maintain the data lake as you want it. You will be working with a variety of use cases and different data sets and will be continuously working on maintaining and keeping the platform live. The report that you will deliver have impact: they are used for sales and forecasting reports and enable our colleagues to work efficiently. You will be taking on various cases, as well as finding answers to questions like these:
- How can we incrementally develop a data platform that enables most optimal development of use cases?
- How can we most efficiently develop a use case on the data platform and incrementally enhance the data platform to accommodate new use cases from our colleagues and our organization?
You make decisions based on facts, instead of guesses. All information within Schuberg Philis will be on the point of your fingertips. In addition, you will also contribute to expanding and maturing the Schuberg Philis data landscape architecture and all its initiatives.
Who are we looking for?
In this role, you will thrive if you have the following experience:
- Experience with building data pipelines in a cloudnative manner (e.g. S3, Lambda’s, Glue)
- You are used to working with large data sets in both data lakes (S3) and data warehouses (Redshift)
- You have good AWS knowledge, especially all the data related services
- You understand the principals of data modeling and data warehousing: creating and designing a data model for reporting purposes
- You have experience with gathering requirements and stakeholder management: creating a data set, processing, and reporting
If you have experience with Spark and Spark Streaming (Java/Scala or PySpark) or Tableau, that would be a big plus.
If you are a strong team player and you recognize yourself in the above, likes to take ownership, can work independently as part of a team and can challenge us on our decisions: we would like to hear from you.