Data Engineer

Assignment description We are looking for a Data Engineer to work with modern cloud-based data platforms and scalable data solutions. In this role, you will work with Databricks, including Apache Spark, Delta Lake, notebooks, job orchestration and performance optimization, as well as Microsoft Azure services such as Azure Data Lake Storage. You will also work with DevOps and CI/CD practices, including version control, automated testing, deployment pipelines and Infrastructure as Code. Qualifications You are comfortable working in the early stages of solution design and contributing throughout the full data engineering lifecycle, from ideation and architecture to development, testing, deployment and operational follow-up. You have a strong understanding of data engineering standards, release processes and quality requirements, including data validation, performance optimization, monitoring and production troubleshooting. You have experience building clean, scalable, resilient and cost-efficient data solutions using cloud-native architectures and modern data platforms, with a strong focus on maintainability and reusability. You have proven experience designing and implementing end-to-end data pipelines for both batch and streaming use cases, including ingestion, transformation and serving layers. You have strong knowledge of data modelling and lakehouse architecture. You have hands-on experience with Databricks, including Apache Spark, Delta Lake, job orchestration, performance tuning and environment management. You have strong knowledge of Microsoft Azure and services commonly used in modern data platforms, such as Azure Data Lake Storage. You have solid experience with DevOps practices, including Git, CI/CD pipelines, automated testing, environment promotion and Infrastructure as Code. You have strong communication skills and can explain data architectures, pipelines and technical trade-offs clearly to non-technical stakeholders.