Top Data & Analytics Jobs in Las Vegas, NV

Design, develop, and optimize SQL-based data solutions and ETL pipelines in Microsoft SQL Server. Ensure data accuracy, performance tuning, validation, and documentation. Partner with delivery, engineering, and client teams, support production systems, participate in code reviews, and drive process improvements with minimal oversight.

Manage client-facing data and analytics projects: define data strategy, build automation and ETL, develop visualizations and predictive analytics, drive transformation, manage scope/budget, and communicate findings to non-technical stakeholders while leveraging finance knowledge.

Design, develop, and optimize Microsoft SQL Server data solutions and ETL pipelines. Build complex T-SQL queries, stored procedures, views, and performance optimizations. Ensure data quality, translate requirements into technical implementations, document logic, support production, and collaborate with delivery, engineering, and client teams.

Lead analytics strategy and delivery for healthcare clients: gather reporting requirements, design and build enterprise data platforms (Databricks/lakehouse), develop and validate reports (including Epic reporting), influence decentralized data teams, and provide post-implementation support and modernization.

Own end-to-end client data migrations: reverse-engineer legacy ETL, design and build Airflow DAGs and Spark jobs, validate and reconcile data at scale, document architecture and decisions, and coordinate cross-functional teams through go-live and hypercare.

Act as a strategic partner to Revenue Operations by analyzing performance, building executive dashboards and reports, improving CRM data quality and governance, supporting forecasting and pipeline management, and designing scalable processes and automations to increase efficiency and revenue visibility.

Build, maintain, and monitor ETL/ELT pipelines in the Microsoft Fabric ecosystem. Implement medallion architecture, transform raw data into analytics-ready models, ensure pipeline reliability and data quality, troubleshoot failures, optimize performance, and support CI/CD and version control for data artifacts.

Design and implement end-to-end cloud data solutions, lead or mentor engineering teams, ensure performance, security, and scalability, integrate diverse data sources, write and optimize SQL, program in Java/Python/Scala, produce presentations and detailed solution documentation, and engage directly with clients to deliver production-ready systems.

Entry-level role supporting data governance and privacy activities: documentation, GDPR support, data quality assessments, control testing, metadata/cataloging, lineage mapping, reporting, stakeholder communications, and training coordination.

Lead a team to manage end-to-end claims data conversion, mapping, validation, and integration into enterprise systems for client onboarding. Oversee multiple concurrent projects, liaise with stakeholders, troubleshoot complex data issues, translate business requirements to technical solutions, and implement process improvements to improve scalability and data quality.