Databricks Data Engineer

Project description: Join our data engineering team as we develop and scale our enterprise data platform. We are building a high-performance ecosystem designed to manage large-scale datasets, ranging from structured to unstructured formats. In this role, you will help modernize our data infrastructure by implementing cutting-edge storage and processing solutions. You will play a key part in designing how we ingest, process, and govern data to provide reliable insights across the organization. Tech stack: • Databricks (Unity Catalog, Delta Live Tables) • Python (PySpark), SQL • Azure, AWS, or GCP • Data Lakehouse, Data Mesh, Data Marts • DevOps, CI/CD Pipelines • Agile (Scrum/Kanban) Requirements: • At least 8 years in Data Engineering, with a minimum of 2 years specifically in Big Data environments. • 4+ years of hands-on experience with Databricks services, including data pipelines and Unity Catalog. • Expert-level skills in Python and SQL. • Strong background in Data Warehousing, ETL, and distributed data processing. • Deep understanding of Data Lakes, Data Warehouses, and Data Mesh concepts. • Experience with at least one public cloud (Azure, AWS, or GCP) and strong design skills for both relational and non-relational storage. • Analytical mindset capable of troubleshooting complex issues in a big data landscape. • Very good verbal and written English B2/C1 • Experience working in Agile (Scrum/Kanban) environments. Main responsibilities: • Design and maintain robust data pipelines and distributed data processing systems using Databricks. • Implement and manage data governance and security frameworks via Unity Catalog. • Develop sophisticated data models (Relational and Non-Relational) to support complex analytical requirements. • Improve the performance and reliability of Big Data workflows and ETL processes. • Work within an Agile environment, integrating DevOps and CI/CD principles into the data lifecycle. • Act as a subject matter expert, guiding the team through complex big data challenges and architectural decisions.