Senior Data Engineer (20187)

La Mesa RV A family owned and operated company, La Mesa RV was founded in 1972. Our original location was in La Mesa, California. We have recently relocated to Phoenix, AZ. Our business philosophy is Customers and Employees are the most important people in the world. Putting this belief into practice has enabled James K, our founder, to guide LMRV on a path of growth and prosperity. LMRV has grown over the years to become one of the largest multi-location RV dealerships in the world and is recognized as a leader in the industry.

Apply to LMRV!! We offer a lot of room to grow internally!

Position Summary

We are seeking a highly skilled Senior Data Engineer to design, build, and optimize enterprise data platforms that enable advanced analytics and AI initiatives. This is a hands-on development role focused on implementing scalable, secure, and high-performing data solutions. The ideal candidate will have deep expertise in data modeling, modern data architecture, data governance, and experience setting up data lakes, lakehouses, and data warehouses. Proficiency in Microsoft Fabric and familiarity with Power BI are essential.

Key Responsibilities

• Design and implement robust data models (conceptual, logical, physical) to support analytics and AI workloads.
• Architect and maintain data pipelines leveraging modern architecture concepts for managing structured and unstructured data.
• Establish and enforce data governance frameworks, including data quality, lineage, metadata management, and compliance.
• Build and manage data lakes, lakehouses, and warehouses using Microsoft Fabric and Azure services.
• Develop and optimize ETL/ELT processes for batch and real-time data ingestion.
• Plan and execute data migration strategies from SQL Server databases to Microsoft Fabric, ensuring data integrity and minimal disruption.
• Collaborate with data scientists, analysts, and business stakeholders to deliver high-quality datasets.
• Integrate data solutions with Power BI for reporting and visualization.
• Ensure compliance with cybersecurity, data privacy, and regulatory requirements.
• Define and enforce best practices for data performance, scalability, and maintainability.
• Implement CI/CD pipelines and automated testing for data workflows.