Location:
Remote (Freelance) Project Duration: 6-12 months THE COMPANY Our client is a recruitment consultancy specialising in IT, Finance, HR, and Digital Technology. Our client is seeking an experienced Data Engineer specializing in Databricks and Treasury Data Lake environments to join a fully remote project. The successful candidate will be responsible for designing, developing, maintaining, and optimizing end-to-end data pipelines within a modern Lakehouse architecture, ensuring reliable, scalable, and high-performance data solutions. This role requires strong hands-on experience with Databricks, DBT, advanced SQL, and enterprise data integration, alongside a solid understanding of data governance, automation, and CI/CD practices. Design, build, and maintain end-to-end data ingestion pipelines integrating multiple source systems.
· Develop and optimize data transformations across bronze, silver, and gold layers within a Databricks Lakehouse architecture.
· Implement automated data quality controls, monitoring frameworks, and alerting mechanisms to ensure data integrity and reliability.
· Design and maintain data models and transformation logic using DBT and advanced SQL.
· Leverage Databricks Lakehouse Federation and Lakeflow Connect to support efficient data integration and accessibility.
· Develop and maintain CI/CD pipelines using GitHub and Azure DevOps,



ensuring controlled deployments, testing, and version management.
· Identify and resolve performance bottlenecks, improving scalability, maintainability, and efficiency.
· Collaborate with business and technical stakeholders to translate requirements into robust data engineering solutions.
· Support data governance standards, documentation, troubleshooting, and release management activities.
· Contribute to analytics and reporting capabilities by delivering reliable, high-quality data products. Proven professional experience as a Data Engineer in enterprise data environments.
· Strong hands-on expertise with Databricks and modern Data Lake/Lakehouse architecture.
· Practical experience developing data transformations using DBT (Data Build Tool) .
· Advanced SQL skills, including query optimization and complex data transformations.
· Experience designing and managing data pipelines across bronze, silver, and gold layers.
· Experience implementing data quality frameworks, monitoring, and automated alerting.
· Familiarity with GitHub, Azure DevOps, and CI/CD processes .
· Understanding of data governance, data modeling, and enterprise integration practices.
· Knowledge of artificial intelligence-related concepts and their application within modern data ecosystems. ·

📌 Data Engineer (España)
🏢 Set Europa
📍 España