Top Senior Data & Analytics Jobs in Las Vegas, NV

Own Kepler’s transaction data feed end-to-end, ensuring accuracy, improving methodologies, developing QA frameworks, solving complex analytical problems, and prototyping enhancements. Analyze massive datasets, automate workflows with AI, evaluate client-facing AI outputs, address high-complexity customer questions, and collaborate with Research, Product, Data Science, and Engineering teams.

Develops credit strategy analysis, portfolio reporting, dashboards, and predictive insights using large datasets. Builds and automates Power BI reporting solutions, identifies credit risk trends, translates business needs into technical specifications, and delivers recommendations to improve credit policy and strategy. Provides analytics consulting, documents processes, supports self-service reporting, and trains non-analytical users. Requires collaboration with stakeholders and independent problem-solving in a banking environment.

Analyze platform, product, customer, advertising, and operational data to generate actionable insights. Build dashboards, reporting frameworks, automated workflows, and scalable analytics pipelines. Evaluate experiments and analytical methodologies, improve forecasting and data accuracy, and partner with product, engineering, marketing, revenue, and leadership teams to influence strategy, customer experience, and platform growth.

Lead data engineering initiatives that build scalable warehouses, pipelines, ETL/ELT processes, dashboards, and automated reporting workflows. Translate finance and operational needs into reliable data solutions, implement governance and quality practices, and support integrations, migrations, acquisitions, and system enhancements across portfolio companies. Partner directly with finance, accounting, analytics, and operational stakeholders to improve decision-making.

Senior Business Intelligence Analyst who develops and governs Power BI dashboards, analyzes clinic performance metrics, ensures reporting accuracy, and translates operational needs into technical requirements. The role manages BI projects end to end, prioritizes analytics tickets, presents insights to executive stakeholders, establishes reporting standards, contributes to data-model requirements, and mentors junior analysts across clinical and corporate operations.

Own end-to-end data platform architecture across ingestion, transformation, modeling, and serving. Improve warehouse efficiency, access control, reliability, observability, orchestration, CI/CD, and developer experience. Lead cross-functional technical initiatives, build monitoring and alerting, mentor engineers, guide architectural decisions, and develop AI-powered data tooling. The role requires strong SQL and Python skills, production experience with Airflow, BigQuery, and containerized infrastructure, plus architectural ownership and stakeholder communication.

Design and optimize Snowflake data warehouses, dbt transformation models, and scalable ETL/ELT pipelines. Develop ingestion utilities, improve SQL and warehouse performance, establish data quality and governance controls, and maintain CI/CD workflows using Git. Collaborate with analysts, data scientists, and business stakeholders across manufacturing, supply chain, and operations. The role also supports modern DataOps practices and may involve orchestration tools and cloud platforms.

Leads enterprise business intelligence and analytics solutions using Power BI and Microsoft Fabric. Designs semantic models, certified datasets, dashboards, DAX calculations, data transformations, security controls, and governed self-service analytics. Assesses and modernizes reporting portfolios, develops predictive and forecasting capabilities, gathers requirements, validates data quality, supports documentation and adoption, and mentors analysts. Collaborates with business, engineering, governance, and security stakeholders to establish scalable enterprise analytics standards.

Lead data architecture for NAVSUP OIS, including database design, data modeling, warehouse strategy, ETL/ELT pipelines, migration, security, retention, backup, recovery, and performance optimization. Coordinate cloud and containerized environments, guide data engineers and DBAs, and support modernization from Oracle to cloud and analytical platforms. The role also provides technical leadership, architecture planning, integration, risk assessment, and policy development for mission-critical systems.

Manages and evolves enterprise data lakes and warehouses, designing scalable AWS-based batch, CDC, and near-real-time ETL/ELT pipelines. Builds data quality, governance, lineage, security, monitoring, and recovery controls; optimizes Spark, Glue, Athena, Redshift, and S3 workloads. Develops reusable Python, SQL, and PySpark frameworks, supports schema evolution and analytical data modeling, and collaborates with business and technical stakeholders to deliver reliable data solutions.