Data Engineer

Marlabs is a global AI and Digital Solutions Consulting firm delivering solutions across AI, data, analytics, and product engineering. The Data Engineer will design, build, and optimize cloud-based data solutions, scalable pipelines, and integrations supporting analytics, reporting, and business intelligence while ensuring data reliability, security, and performance.

Responsibilities:

• Design, develop, and maintain scalable data pipelines, ETL/ELT workflows, and data integration processes to support enterprise reporting and analytics needs
• Build and optimize data transformation solutions using Python and SQL, ensuring efficient processing of large and complex datasets
• Integrate data from multiple internal and external sources while maintaining data quality, consistency, lineage, and reliability across the data platform
• Develop and support cloud-based data solutions within Azure, leveraging modern data services and best practices for scalability and performance
• Contribute to data platform modernization initiatives, including the implementation and adoption of Microsoft Fabric and Lakehouse architectures
• Collaborate with architects, analysts, business stakeholders, and engineering teams to deliver trusted, business-ready data solutions aligned with organizational objectives
• Optimize data models, storage layers, and query performance to support high-volume analytics and reporting workloads
• Troubleshoot and resolve data pipeline, integration, and platform-related issues while implementing monitoring, governance, security, and compliance standards

Requirements:

• 5+ years of experience in Data Engineering, including the design, development, and support of enterprise data platforms and data integration solutions
• Strong proficiency in Python and SQL, with experience developing complex transformations, data models, performance optimizations, and large-scale data processing solutions
• Hands-on experience with Azure data services, including Azure Data Factory, Synapse Analytics, Azure Storage, Databricks, or related cloud technologies
• Proven experience building and maintaining ETL/ELT pipelines, data warehouses, and cloud-based analytics environments supporting reporting and business intelligence initiatives
• Strong understanding of data modeling, data warehousing, governance, security, and modern data architecture principles, including Lakehouse and cloud-native data platforms
• Hands-on experience with Microsoft Fabric, modern Lakehouse architectures, and regulated or compliance-driven data environments