Top Data & Analytics Jobs in Las Vegas, NV

Build and maintain analytics solutions for cloud technology and network infrastructure teams. Responsibilities include gathering requirements, automating reporting, developing self-service analytics, maintaining data pipelines and models, querying multiple data sources, and communicating insights through dashboards and reports. The role supports data-driven planning, capacity management, colocation, and finance decisions while collaborating with technical and business stakeholders.

Analyze customer behavior, forecasts, market share, retention, revenue growth, and operational performance. Develop analytics frameworks, use Tableau and Snowflake with cross-functional analytics teams, apply AI-enabled workflows, and communicate actionable recommendations to leadership to support staffing, prioritization, and strategic decision-making.

Designs, develops, and maintains scalable data pipelines, data warehouses, databases, and analytical systems. Responsibilities include ETL implementation, data modeling, performance monitoring, troubleshooting, infrastructure optimization, process automation, and collaboration with cross-functional teams to support reporting and analytics. Requires 5+ years of data engineering experience and a relevant bachelor’s degree. Financial services experience is preferred.

Analyze complex data to support business decisions across marketing, finance, product, sales, medical affairs, and customer success. Responsibilities include defining data requirements, developing and automating data pipelines, building interactive dashboards, identifying trends and process improvements, and presenting insights to executives and external partners. The role requires advanced SQL, Python, BI, visualization, and cross-functional analytics experience, with an emphasis on using AI to improve efficiency.

Leads market research and insights partnerships across operating groups, shaping research agendas and translating qualitative and quantitative findings into strategic recommendations. Manages and develops insights analysts in a matrixed environment, allocates resources across portfolios, oversees research quality and methodology, and presents actionable findings to executive stakeholders. Requires advanced research, statistical analysis, survey design, storytelling, stakeholder influence, and project management expertise.

Supports PMI’s research agenda through survey, qualitative, secondary, quantitative, business analysis, and foresight research. Analyzes AI, technology disruption, macroeconomic, industry, and future-of-work trends; translates complex findings into executive-ready insights, narratives, thought leadership, and strategic recommendations. The role requires rigorous methodology, independent initiative, cross-functional collaboration, strong communication, and the ability to assess technical developments and their business implications.

Leads enterprise Business Intelligence strategy, architecture, governance, security, and self-service analytics adoption. Architects solutions across Power BI, Tableau, SAP BusinessObjects, and Databricks; establishes semantic models, data standards, DevOps, CI/CD, and reporting performance practices. Partners with executives and technical teams to modernize analytics platforms, reduce manual reporting, and enable AI-ready decision-making. Mentors BI professionals and drives enterprise data literacy and analytics transformation.

Design, develop, and maintain scalable ETL/ELT data integration pipelines supporting analytics, reporting, and product capabilities. Build ingestion, transformation, validation, and curated data layers; optimize production workflows; document systems; and implement data quality monitoring and testing. Collaborate with implementation, engineering, analytics, and customer success teams to resolve data issues, support onboarding, and ensure reliable, accessible data.

Designs, develops, and maintains scalable ETL/ELT pipelines and data platform capabilities for high-volume healthcare data. Responsibilities include complex SQL development, Airflow orchestration, dbt transformations, data quality frameworks, pipeline monitoring, troubleshooting, performance optimization, and documentation. The role collaborates with Data Operations, Product, Analytics, Data Science, and clinical teams to deliver reliable data for analytics, reporting, product features, and AI/ML initiatives.

Develops business intelligence dashboards, reports, data models, and queries to support data-driven decision-making. Translates business requirements into visualizations, documents requirements and deployment processes, supports existing dashboards and applications, and provides end-user training and technical support. Collaborates with business intelligence and transformation teams to improve member and employee experiences.

Analyzes business performance data and delivers actionable insights for stakeholders and senior leaders. Develops dashboards, scorecards, KPI reports, and recurring brand reporting while ensuring data accuracy and reliability. Partners with sales, marketing, product, and technical teams to translate business needs into analytics solutions. Performs ad hoc analysis, identifies trends and risks, supports executive presentations, and communicates recommendations clearly.

Analyzes e-commerce performance, sales, conversion, traffic, profitability, digital shelf metrics, POS data, consumer behavior, and market trends. Builds executive dashboards and recurring reports, conducts forecasting and ad hoc analyses, and translates insights into recommendations for marketing, merchandising, product development, and channel strategy. Partners with cross-functional stakeholders to identify growth opportunities, improve processes, and support strategic business decisions.

Analyzes customer experience, survey, operational, CRM, ERP, support, and financial data to build unified customer views and actionable insights. Responsibilities include cohort analysis, segmentation, predictive modeling, revenue attribution, CX dashboards, reporting automation, and closed-loop action tracking. The role partners with IT, data teams, Finance, and business stakeholders to improve data quality and translate complex analyses into executive recommendations supporting retention, expansion, and customer experience improvements.

Architect and lead enterprise data platforms, pipelines, and infrastructure using Spark, Databricks, and cloud technologies. Build scalable data models and dimensional schemas, establish governance and data quality frameworks, optimize performance and reliability, and implement monitoring. Partner with stakeholders to translate requirements into technical solutions, lead design reviews, mentor engineers, contribute to platform strategy, troubleshoot complex failures, and support hiring and team development.