Top Remote Analysis Reporting Jobs in Las Vegas, NV

Lead and grow the Revenue Analytics team to deliver strategic sales and customer lifecycle insights. Build forecasting, pipeline, capacity, predictive models, and customer lifecycle analytics to improve revenue, retention, adoption, and expansion. Partner with GTM, Finance, Product, and Enterprise Data to create executive reporting, data governance, AI-enabled self-serve datasets, and integrated analytics that drive business outcomes and support a shift to consumption-based models.

Own Silver and Gold medallion-layer modeling and semantic layer governance using dbt and SQL. Improve warehouse performance and cost, standardize BI tooling, collaborate with stakeholders to produce trusted metrics, troubleshoot data quality, and evolve analytics platform.

Owner of the analytics foundation: design and maintain BigQuery/dbt models, pipelines, and Looker Studio reporting; build AI workflows and web apps on GCP; integrate marketing, e-commerce, and fulfillment data; ensure GCP ops, security, and reliability; use AI-assisted tools daily and collaborate with business and client stakeholders.

Manage analytical service operations by overseeing a team, designing software for data mining, developing statistical models, and generating insights for marketing outcomes. Provide training and mentorship to direct reports.

Gather and document business and functional requirements, analyze processes, recommend improvements, produce BRDs/FRDs/user stories and process maps, support solution design, UAT, testing and deployment, produce reports/dashboards, monitor project progress, and support change management and stakeholder communication.

Lead implementation and configuration of Adobe Analytics and Adobe Target across web and mobile, design tagging and data architecture, translate business needs into tracking requirements, troubleshoot data collection issues, integrate with CDP (Hightouch), document data dictionaries, and drive adoption of analytics across cross-functional teams.

Build and maintain scalable data pipelines and Python automations for ingesting, processing, and enriching data. Integrate SaaS sources via APIs, use Databricks/PySpark/Delta Lake and AI tools to power lead generation, enrichment, deduplication, and entity resolution. Collaborate cross-functionally to translate business needs into automated, production-ready solutions.

Develop and maintain large-scale, cloud-native data services and distributed pipelines for multi-tenant healthcare systems. Responsibilities include data modeling, database component development, SQL programming, performance tuning, testing, deployment, code reviews, proof-of-concepts, and full software development lifecycle ownership. Collaborate with global engineering teams, evaluate technologies, apply security and operational requirements, and use AI tools to accelerate development.

Owns end-to-end development and maintenance of Tableau and Amazon QuickSight dashboards for operational and executive stakeholders. Translates business needs into datasets, visualizations, and actionable insights; writes SQL for analysis and validation; collaborates with data engineers on AWS lakehouse sources; optimizes performance, validates data quality, documents dashboards, and continuously improves the BI portfolio.

Leads enterprise data architecture strategy, modernization, and multi-year platform roadmaps. Defines standards for data models, ingestion, transformation, orchestration, quality, governance, observability, and consumption across batch and streaming environments. Provides technical leadership to data engineering and analytics teams, oversees scalable data solutions, mentors technical leaders, and partners with business, engineering, security, and data science stakeholders. Evaluates technologies, guides vendor selection, enables data products, and explores GenAI applications.

Build and scale an enterprise metrics store, dbt models, semantic-layer definitions, and analytical workflows. Develop governed business metrics, root-cause analysis, metric relationships, and reusable logic for BI tools. Partner with product, engineering, sales, underwriting, claims, and experience teams to translate business questions into actionable insights. Improve data quality, define data contracts, debug upstream and analytical issues, and help prepare metric infrastructure for API-based serving.

Lead infrastructure analytics for compute, storage, and networking: design scalable data pipelines, define core metrics, build dashboards and APIs, ensure data quality and governance, drive instrumentation fixes, and advise executives on capacity, utilization, and readiness.

Develops scalable business intelligence and analytics solutions for Microsoft’s cloud data center delivery lifecycle. Builds data assets, dashboards, models, and automated workflows; improves data quality and reporting; translates complex business questions into analytical requirements; identifies process improvements; and delivers actionable insights to technical and executive stakeholders through cross-functional partnership.