Data Engineer

Role Overview: As a Data Engineer, you will help to shape Cargoo’s data engineering strategy and guide the design, architecture, and implementation of scalable data solutions. You will work with teams across the company to identify data opportunities to drive impact, understand their needs, and help them get the most out of our Data Platform. Problem space: Data infrastructure today is still largely: data models that don’t scale with business complexity engineering and business teams working in silos reliability and quality issues discovered too late legacy systems coexisting with modern data tools What you will be doing: shaping Cargoo’s data engineering strategy end-to-end building and evolving a Data Platform that powers analytics, ML/AI, and real-time decisions collaborating across engineering, BI, and business to turn data needs into robust solutions identifying opportunities across the organisation to maximise value from data assets What we expect from you: Solid proficiency in Python (runtime environment, package management) and SQL (DML, DDL). Hands-on experience with SQL Server / Azure SQL Server. Experience working with cloud platforms, preferably Microsoft Azure. Familiarity with the modern data stack, including tools such as dbt and orchestration frameworks (Airflow, Dagster, or similar). Strong understanding of ETL/ELT concepts, data architecture, and data modelling. Experience with streaming technologies (Kafka or equivalent). Experience with Docker and container orchestration technologies. Experience deploying and monitoring applications on Kubernetes (K8s). Knowledge of application lifecycle management. Understanding and application of DataOps practices. Strong project management, execution skills, and a clear sense of ownership and accountability. What you won’t find here: over-engineered architecture for the sake of it data pipelines nobody monitors or maintains silos between engineering and the rest of the business If this resonates with you – let’s talk!