Top Senior Data & Analytics Jobs in Las Vegas, NV

Analyze complex datasets, develop data models, dashboards, and visualizations, and conduct predictive and statistical analysis for client decision-making. Collaborate with clients to deliver tailored analytics solutions, maintain data integrity, communicate insights through reports and presentations, and support data-driven operational strategies using SAS, Power BI, Tableau, and SQL tools.

Develop and maintain enterprise Power BI dashboards and complex SQL solutions supporting operational finance. Design dimensional data models, optimize large-data performance, perform in-depth analysis and ad-hoc reporting, use Python for automation, troubleshoot data quality and performance, and provide technical leadership and mentoring to improve analytics and reporting capabilities.

Analyze observability, digital experience, and business analytics data for enterprise clients to improve website performance and user engagement. Manage relationships with 4–8 clients, conduct ad hoc analyses, configure Dynatrace solutions, create reports and dashboards, present findings to technical and executive audiences, provide training, and influence product roadmap decisions. The role combines advanced data analysis, strategic consulting, customer account management, and executive communication.

Designs and delivers large-scale, governed data pipelines and infrastructure across the full data lifecycle. Responsibilities include coding in Python and SQL, optimizing Airflow, dbt, AWS, Kafka, and Iceberg/Parquet workflows, implementing data quality and observability, contributing to architecture and tool evaluations, mentoring engineers, collaborating with stakeholders, and participating in on-call support.

Lead a GTM Analytics team supporting Marketing, Sales, RevOps, and Customer Operations. Manage embedded analysts, establish trusted reporting and QA processes, review SQL and dashboards, guide funnel, campaign, sales, support, forecasting, segmentation, attribution, and experimentation analysis, and deliver executive recommendations. Partner with GTM leaders and data engineers, coach analysts, and develop self-service analytics, automation, governed dashboards, metric documentation, and AI-assisted workflows.

The Senior Analytics Engineer will design and implement scalable data solutions for Finance Analytics, reconcile data accuracy, and collaborate across teams to enhance financial datasets and reporting workflows.

Build and maintain sales KPI dashboards, perform recurring and ad-hoc sales performance analyses, model efficiency drivers (churn, LTV:CAC, pipeline coverage), create executive insights, partner with GTM leaders, and automate/reporting processes to scale Sales operations.

Owns RTB House’s performance media measurement strategy across products. Responsibilities include defining measurement taxonomies, evaluating attribution, incrementality, MMM, and MTA methodologies, managing third-party measurement partners, developing testing playbooks, piloting identity and measurement approaches, translating insights into market-facing messaging, and training commercial teams. The role requires hands-on performance media buying or oversight experience and strong ability to communicate measurement concepts, limitations, and results to technical, executive, and commercial audiences.

Leads a team of five experienced analysts and data scientists while personally owning strategic analytics across ecommerce, health, supply chain, inventory, fulfillment, and merchandising. Partners with executives, establishes KPI and reporting standards, prioritizes the analytics roadmap, and delivers actionable business insights. The role also advances AI-native, self-service analytics capabilities, strengthens data governance and quality, and builds a high-performing analytics culture.

Lead the architecture and migration of Rula’s data platform to Snowflake and Medallion architectures. Govern warehouse performance and cloud costs, establish data contracts and intake guardrails, and enforce GitHub-based CI/CD testing for data quality and query performance. Scale AI-assisted engineering practices across teams while partnering with executives and domain engineers. The role also supports secure clinical data handling, schema evolution, semantic BI integrations, and production ELT pipeline development.