Data Engineer

Marlabs Inc.; Indiana; On-site; USD 100,000 - 150,000; Full time

Job summary

`Marlabs Inc.` is seeking a Data Engineer to design, build, and optimize cloud-based data pipelines supporting analytics and BI initiatives. You will leverage Python, SQL, and Azure data services to develop scalable data solutions and ensure data quality and governance across enterprise ecosystems.

The ideal candidate has 5+ years of experience in data engineering, strong data modeling skills, and hands-on exposure to modern data platforms including Lakehouse architectures and Microsoft Fabric.

Qualifications

• Minimum 5+ years of Data Engineering experience building enterprise data platforms.
• Strong Python and SQL development for complex transformations and large-scale processing.
• Hands-on experience with Azure data services and cloud-native architectures.

Responsibilities

• Design, build, and optimize cloud-based data pipelines to support analytics and BI initiatives.
• Develop and maintain ETL/ELT processes and data models for scalable data warehouses.
• Ensure data quality, governance, security, and compliance across the data platform.
• Collaborate with architects, analysts, and stakeholders to deliver trusted, business-ready data solutions.

Skills

Python

SQL

Azure

Data Modeling

ETL/ELT

Education

Bachelor's degree in Computer Science or related field

Tools

Azure Data Factory

Synapse Analytics

Databricks

Lakehouse

Job description

Marlabs, a global AI and Digital Solutions Consulting firm, delivers intelligent solutions across AI, data, analytics, and product engineering. Since 2000, we have partnered with some of the largest healthcare, life sciences, financial services, and government organizations worldwide. As we continue to expand our global footprint, we have an exciting opportunity for a highly skilled Data Engineer to join our innovative and dynamic team.

Data Engineer | About You

As a Data Engineer, you will be responsible for designing, building, and optimizing modern cloud-based data solutions that support analytics, reporting, and business intelligence initiatives. You will leverage your expertise in Azure, Python, SQL, and modern data platforms to develop scalable data pipelines, integrate data from multiple sources, and ensure the reliability, security, and performance of enterprise data ecosystems. The ideal candidate combines strong technical data engineering skills with experience in cloud-native architectures, data transformation, and modern analytics platforms, including Microsoft Fabric.

Data Engineer | Day-to-Day

• 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.

Data Engineer | Skills & Experience

• 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.
• Preferred: Hands-on experience with Microsoft Fabric, modern Lakehouse architectures, and regulated or compliance-driven data environments.