Top Remote Analysis Reporting Jobs in Reno, NV

Lead technical strategy and roadmap for an enterprise Databricks-based data platform. Drive governance, metadata, lineage, and semantic layer standards; build reusable data products; enable self-service analytics and scalable ML operations; mentor engineers and align platform investments with business outcomes.

Investigate and analyze suspected fraud cases, monitor and validate fraud strategies, develop countermeasures, evaluate risk scenarios, and collaborate cross-functionally to improve fraud detection and minimize false positives/negatives.

Build data foundations and end-to-end pipelines, research and implement quantitative pricing, market-making, and risk models for prediction markets, model cross-market dependencies and parlays, develop backtesting/simulation frameworks, monitor model performance and collaborate closely with traders to improve pricing and trading outcomes.

Lead a distributed SQL team and own the end-to-end service model for custom analytics: intake, scoping, delivery, QA, documentation, and SLAs. Serve as a customer-facing technical lead, build scalable workflows and request taxonomy, partner cross-functionally, and balance customer delivery with internal platform priorities.

Own and evolve the analytics platform: build and maintain dbt data models, govern semantic metrics in Lightdash, ensure data quality and observability, and partner with analysts and stakeholders to enable reliable self-service reporting.

Lead enterprise data platform strategy and architecture, define data standards and governance, drive Snowflake maturity, oversee legacy data migrations, design ingestion and DataOps patterns, and enable analytics, reporting, AI, and reusable data products across the organization.

Lead development and governance of the supply chain data warehouse and analytics platforms. Build SQL-driven models, dashboards, and KPIs to drive inventory optimization, cost reduction, supplier performance, and working capital improvements. Support ERP integrations and data migrations, perform deep data discovery and predictive analytics, and present actionable insights to senior leaders to enable strategic decision-making.

Own analysis, validation, and documentation of enterprise platform workflows and data inputs. Define test strategies, lead functional/regression validation, approve configuration changes, and drive remediation. Partner with engineering/product to ensure platform reliability, data quality, and release readiness while applying AI-enabled tools to improve efficiency.

Build and maintain Quince's compensation data environment: integrate HR systems, automate benchmarking and AI workflows, support comp reviews and equity approvals, analyze pay trends, and partner with Talent, Finance, and Legal on global comp strategy.

The Staff Data Engineer will lead financial data operations, ensuring accuracy and reliability of data pipelines, while collaborating with Finance, Product, and Engineering teams to enhance systems and decision-making processes.