Senior Data Engineer – SQL Data Lake & Data Warehouse Optimization - 2-3 Months Contract

Company Description Vistas Cloud is a Microsoft Solutions Partner and trusted Microsoft Cloud Solutions Provider. We specialize in Dynamics 365 and Microsoft cloud consulting, delivering modern, cloud‑based solutions that solve real business challenges and align technology with strategic goals. Our team is recognized for helping organizations streamline operations and unlock value through tailored Microsoft platforms and data solutions. Role Description Vistas Cloud is seeking a Senior Data Engineer to own the performance, reliability, and governance of our SQL‑centric data lake and data warehouse. In this role, you will assess existing data structures and pipelines, surface and resolve bottlenecks, and implement improvements so internal teams, analysts, and clinicians can trust and efficiently use our data assets. This is a 2–3 month contract position, fully remote, and open to candidates based in the United States. You will collaborate closely with cross‑functional stakeholders to design and maintain data models, optimize our lake and warehouse environments, manage ETL/ELT processes, and support a wide range of analytical needs. Responsibilities • Analyze and optimize SQL‑based data lake and data warehouse structures, queries, and pipelines for performance, reliability, and cost. • Design, refine, and document scalable data models to support analytics, reporting, and downstream applications. • Build and maintain robust ETL/ELT workflows, ensuring data is accurate, timely, and well‑governed across environments. • Partner with analysts and business stakeholders to understand requirements and translate them into efficient data solutions. • Implement and promote best practices for SQL development, version control, testing, and monitoring of data pipelines. Qualifications • Proven experience in Data Engineering with a strong focus on SQL and modern database platforms. • Advanced SQL capabilities, including query tuning, indexing strategies, partitioning, and working with large fact and dimension tables. • Strong skills in data modeling and the design and optimization of scalable data infrastructure. • Hands‑on experience with ETL/ELT processes and tools. • Deep knowledge of data warehousing concepts and their application to business intelligence and analytics use cases. • Solid understanding of modeling patterns such as star and snowflake schemas, slowly changing dimensions, and lakehouse layers (bronze/silver/gold). • Familiarity with data analytics workflows and how engineering decisions support reporting and decision‑making. • Excellent problem‑solving skills and the ability to diagnose and resolve complex technical issues.