Senior Data Engineer | Azure Data Platform & Lakehouse

Marlabs Inc.; Northern (KY); Hybrid; USD 90,000 - 150,000; Full time

Job summary

Marlabs Inc. is seeking a Data Engineer to design, build, and optimize cloud-based data solutions that support analytics across the enterprise. You will leverage Python, SQL, and Azure data services to develop scalable pipelines and reliable data ecosystems.

The role emphasizes data transformation, data integration from multiple sources, and ensuring data quality and security while contributing to modernization efforts including Microsoft Fabric and Lakehouse architectures.

Qualifications

• 5+ years of experience in Data Engineering or related field.
• Proficiency with Python and SQL for complex transformations and data modeling.
• Experience with cloud-based data platforms and modern analytics environments.

Responsibilities

• Design, develop, and maintain scalable data pipelines, ETL/ELT workflows, and data integration processes for enterprise reporting and analytics.
• Build and optimize data transformations using Python and SQL for large and complex datasets.
• Integrate data from multiple sources while preserving quality, lineage, and reliability across the data platform.
• Develop and support cloud-based data solutions within Azure, utilizing data services for scalability and performance.
• Contribute to data platform modernization, including Microsoft Fabric and Lakehouse architectures.
• Collaborate with architects, analysts, stakeholders, and engineering teams to deliver trusted, business-ready data solutions.
• Optimize data models, storage layers, and query performance for high-volume analytics.

Skills

Python

SQL

Azure cloud

Data integration

Tools

Azure Data Factory

Synapse Analytics

Databricks

Microsoft Fabric

Job description

Marlabs Inc. is seeking a Data Engineer to design, build, and optimize cloud-based data solutions that support analytics across the enterprise. You will leverage Python, SQL, and Azure data services to develop scalable pipelines and reliable data ecosystems.

The role emphasizes data transformation, data integration from multiple sources, and ensuring data quality and security while contributing to modernization efforts including Microsoft Fabric and Lakehouse architectures.