Senior Data Engineer

About the role

Design, build, and maintain scalable batch and streaming data pipelines using Apache Spark and cloud-native data technologies.

• Develop and optimize ETL/ELT workflows to ingest, transform, and curate data from diverse source systems into analytics-ready datasets
• Implement data modeling and transformation logic to support reporting, dashboards, and downstream analytical and machine learning workloads
• Build and manage data processing workloads within modern lakehouse platforms
• Ensure data quality, reliability, and consistency by implementing validation checks, monitoring, and reconciliation processes
• Optimize Spark jobs for performance, cost efficiency, and scalability across large and complex datasets

Requirements

• Strong experience as a Data Engineer building and operating production data pipelines
• Hands-on experience with Apache Spark for large-scale data processing
• Proficiency in Python, SQL, and data transformation best practices
• Experience with cloud-based data platforms and storage (e.g., Data Lakes, Lakehouse architectures)
• Familiarity with Microsoft Fabric, OneLake, or similar analytics platforms (strong plus)
• Experience designing and optimizing data models for analytical workloads

Benefits

• Opportunity to work on scalable, reliable, and high-performing data pipelines
• Collaborative environment with analytics engineers, data scientists, and product teams
• Contribute to Agile delivery processes