Senior Data Engineer
Skills
About the role
Senior Data Engineer & Data Modeler - English speaking
Role Overview
We are seeking an experienced Data Engineer & Data Modeler to design, build, and optimize our next-generation data ecosystem. In this role, you will split your focus between architectural data modeling and robust pipeline engineering, leveraging Databricks and Microsoft Fabric to deliver enterprise-grade analytics solutions.
Key Responsibilities
Dual-Focus Engineering & Modeling: Architect robust dimensional data models (Star and Snowflake schemas) while concurrently engineering the end-to-end data pipelines that feed them.
Modern Lakehouse Architecture: Build, deploy, and optimize scalable Spark/PySpark data pipelines within both Databricks and Microsoft Fabric environments.
Advanced Data Transformation: Develop complex, high-performance SQL and PySpark scripts for data transformation, validation, and multi-layer aggregation (Medallion architecture).
Data Governance & DevOps: Implement automated data quality frameworks, manage CI/CD deployment workflows, and maintain comprehensive metadata documentation.
Performance & Cost Optimization: Monitor, tune, and optimize Spark jobs and compute clusters to balance high performance with cost efficiency.
Core Requirements
Experience: 5–7 years of proven experience bridging the gap between advanced data modeling and data pipeline engineering.
Platform Expertise: Strong hands-on experience developing within Databricks and Microsoft Fabric.
Technical Skills: Mastery of Spark / PySpark and advanced SQL for complex data manipulation.
Best Practices: Deep understanding of data warehousing concepts, data quality tracking, DevOps, and CI/CD practices in a cloud environment.
Soft Skills: Strong technical ownership, analytical problem-solving abilities, and clear communication skills.
Questions about this role
Want AI Applyd to auto-apply to roles like this?
We tailor your resume per posting, fill the forms, and track replies for you.