About this role
Select which cookies you accept Strictly necessary Data & Engineering · TBAuctions | Amsterdam · Hybrid Data Engineer We usually respond within a week Every auction generates data: lots, bids, bidders, logistics, valuations, payments. Nine brands means nine sets of different systems, conventions and quirks. The Data team's job is to maintain a Data Platform that ingests said data to enable it's usage, transformation, and eventually value generation. What you will do You'll join an established Data Team as a Data Engineer, working alongside fellow Analytical Engineers and Data Analysts, building and running the pipelines and infrastructure that move data from a variety of different systems (e.g. Services such as Bloomreach, API sources and a variety of databases) into Databricks and out to the people and products that use it. This is a hands-on engineering role with real ownership. You'll pick up components end to end, from the conversation with the stakeholder about what they actually need, through the design, to the provisioning of the infrastructure, ending with the orchestration of the different processes in a reliable, visible and cost-effective way. This is also a role where new systems can and will come into play. Being able to integrate said systems into the Data Platform in a modular manner that upholds the strengths and principals of the platform while delivering the intended value is a key challenge. Key Responsibilities - Build and maintain ETL data pipelines in Python, orchestrated with Airflow, processing data in Databricks on Azure - Define infrastructure as code with Terraform, and ship it through Azure DevOps pipelines with shared libraries published as Artifacts - Build and integrate APIs (FastAPI or similar) to make data available to other teams and services - Containerize workloads with Docker and keep them running reliably in production - Write the design down before you build it: architecture diagr...