EU remote
Senior Data Engineer
About this role
Joining Collibra’s Data Office Team Collibra is looking for a Senior Data Engineer in our own Data Office to evolve our internal self-serve data platform and to optimize data flow and collection for cross functional data products. This role will be integral to supporting Collibra’s rapid growth and our thought leading position in data intelligence. This is a hands-on, roll up your sleeves position and requires a passion for data and engineering.
You communicate as comfortably with technical stakeholders as with business ones. You are unable to shed a continued enthusiasm for new (data) technology. You pride yourself in providing a self-service, production-ready data platform that, following best practices, keeps the lights on for the business’ data products. As you fuel Collibra’s modern Data Platform, you will leverage your experience to lead self-serve data infrastructure into state of the art platform and help data teams across Collibra drive change through data.
This is a hybrid role based in our Brussels office. Our hybrid model means you’ll work from the office at least two days each week. This setup helps us stay connected, work more closely together, and keep making progress as a team. Senior Data Engineers at Collibra are responsible for Continuously evolve our self-service data infrastructure for our business’ data products Manage, provide support and use extraction and transformation tools to enable data product owners to drive business value Manage and build cloud infrastructure technology to deliver value for the business and elevate data security Collaborate and support stakeholders (in Finance, Marketing, Product, Sales, …) to identify and plan new requirements for our data platform and data products You have 5+ years experience performing data engineering operations to fulfill business needs with a strong focus on data modeling Strong experience in building cloud-based data infrastructures in GCP using IaC (Terraform).
In depth knowledge of warehousing (BigQuery) and storage technologies. Experience with orchestration tools (Apache Airflow), scheduling of ETLs and strong programming skills in Python and SQL (with dbt). Familiarity with running containerized workloads using Docker and Kubernetes Interest in applying AI/LLM tooling to data engineering workflows is a plus Interest in making sure our data assets are governed, documented, and discoverable.