Top Senior Data & Analytics Jobs in Las Vegas, NV

Design, build, and maintain cloud-based ELT data pipelines and analytics-ready datasets using Snowflake, dbt, and integration tools (Fivetran/Airbyte). Implement CDC and incremental loading, optimize Snowflake performance, enforce data quality and monitoring, create dimensional models for reporting, enable CI/CD for dbt projects, and collaborate with analytics and stakeholder teams to support reporting and advanced analytics.

Produce executive-grade briefs from cross-functional research and listening programs under compressed timelines. Shape questions, synthesize quantitative and qualitative evidence, craft recommendations and visuals for C-suite and Board, coach analysts, and track briefing-driven decisions to close the loop.

Design and manage VoC instruments and recurring feedback programs, ensure data quality, synthesize insights, and own the insights repository, decisions journal, and methodology library. Partner with VoC and KM vendors, run institutional-memory rituals (intake, closeout, handoffs), coach peers on VoC craft and documentation, and maintain taxonomy and metadata for enterprise-scale reuse.

Lead research and listening for a specific audience: design and run primary research, integrate listening signals, synthesize quantitative and qualitative insights, and deliver timely, decision-oriented recommendations while coaching analysts and partnering with enterprise stakeholders.

Bridge enterprise customers' legacy BI to Hightouch by reverse-engineering complex marketing reports, building reusable reporting frameworks, engineering and documenting semantic/context layers, ensuring accurate SQL generation, and training non-technical marketers while collaborating cross-functionally to deliver reliable, idempotent AI-driven analytics.

Design, build, and maintain dbt data models and scalable ELT pipelines; optimize performance-aware SQL on Snowflake; ensure observability, testing, and CI/CD; partner with product and engineering teams to meet analytic needs, mentor engineers, document business logic, and troubleshoot ingestion, transformation, and warehouse issues.

Drive enterprise automation by identifying workflow inefficiencies across Home Health, Primary Care, and Pharmacy. Use data analysis, process and journey mapping, and MDM to define opportunities and leading indicators. Partner with product, engineering, clinical, compliance, and operations to design, validate, and scale AI-enabled automation solutions that improve outcomes and efficiency while ensuring regulatory compliance.

Perform Ukrainian- and English-language open-source research and document review to assess KYC, sanctions, AML, and supply chain risks. Use Exiger's DDIQ and shipping databases to identify risk-relevant information, produce client-ready narratives, onboard and train users, and advise on tool usage. Support U.S. government clients with timely, accurate due diligence and risk assessments.

Lead full-stack analytics at Air by designing and maintaining dbt models and BigQuery transformation layer, ensuring data quality and observability, owning ingestion/orchestration, building self-serve BI (Mode/Hex) and AI-native interfaces, and partnering with product, growth, and GTM teams to deliver trusted data products and strategic insights.

Build and maintain dbt data models, design BI dashboards and reports (Count and other tools), and deliver merchant/issuer analytics. Partner with GTM and product teams to translate data into actionable insights, improve data quality, and lead technical investigations to scale analytics infrastructure.

Design, build, and maintain scalable data pipelines, data models, ETL/ELT, and BI solutions. Collaborate with data scientists and stakeholders to improve data quality, accessibility, and PHI security. Develop and document workflows, optimize processing/storage, support data warehouse and visualization, and adopt AI tools to drive data-informed outcomes.

Build and maintain scalable monitoring solutions and dashboards to track production, campaign, and operational data. Analyze large-scale datasets to detect anomalies, perform root-cause investigations with Engineering and Production Operations, and deliver actionable insights to improve platform reliability and operational efficiency.