Top Data & Analytics Jobs in Reno, NV

As a Staff Product Analyst, you'll define analytics strategies, build measurement infrastructure, design experiments, and partner with product teams to boost self-serve conversion and product adoption.

The Senior Analytics Engineer will develop data pipelines, build models, and create dashboards to provide actionable insights for various teams. The role requires collaboration with multiple stakeholders to meet analytical needs and ensure data governance.

Lead GTM data governance and strategy to improve Salesforce and GTM system data quality, ownership, and usability. Define KPIs linking data quality to pipeline/forecast accuracy, drive adoption of standards and scorecards, prioritize data improvements, lead cross-functional implementations, and build a team to scale revenue-impacting data practices.

Design, build, and operate large-scale data platforms and Spark/PySpark pipelines. Enable data integration, modeling, quality, and observability. Build MCP servers and AI-augmented tooling, mentor engineers, and lead cross-functional projects to deliver reliable data products.

Build and maintain dbt models, write SQL to investigate and validate data, implement data quality checks, document lineage and metrics, resolve production issues (including on-call), and partner with analysts and business teams to deliver production-ready data products using modern warehouse tooling and AI-assisted frameworks.

Partner with Customer Success and CS Ops to build post-sales analytics: customer health scoring, renewal and renewal pipeline reporting, billing and support signal analysis, and expansion/upsell dashboards. Own dashboard ecosystem, translate stakeholder requests into scalable reporting, collaborate with Finance and Data Engineering, and leverage AI tools to accelerate analytic workflows and maintain data quality for retention and expansion decision-making.

Partner with Sales, RevOps, Finance, and Data Engineering to convert CRM and pipeline data into actionable insights. Build and maintain pipeline and forecasting reports, dashboards, and metrics; identify risks and opportunities; improve data quality and reporting reliability; triage analytics requests; and embed AI tooling into analytics workflows to accelerate output and ensure analytical rigor.

Own and architect large-scale data pipelines, orchestration, and integrations. Drive IaC strategy (Terraform), third-party API and AI/LLM tool integrations, build export pipelines and internal tooling, mentor engineers, and align cross-team technical strategy for reliable, scalable data infrastructure.

The Enterprise Data Architect will design and govern data architecture, create enterprise data models, and ensure data consistency across various systems.

Lead CX analytics strategy and operations by standardizing metrics, enabling self-service analytics, and embedding AI in the analytics lifecycle to enhance decision-making processes.

Lead end-to-end COGS and gross margin analysis for hardware and software products, model cost-saving scenarios, answer ambiguous executive questions, partner with data engineering/finance/product, build reliable datasets and analytical frameworks, and present recommendations to C-suite stakeholders.

Lead and manage a team of data engineers to develop and maintain data pipelines and warehouses, ensuring data quality and adherence to best practices.