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, pipelines, integrations, and transformation workflows using Azure, Python, SQL, and modern data platforms. The role also involves supporting analytics and reporting, ensuring data reliability and security, and contributing to Microsoft Fabric and Lakehouse modernization initiatives.

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