Top Remote Analysis Reporting Jobs in Reno, NV

Design and scale fraud-mitigation strategies for buyer, seller, and account fraud across Stripe products. Monitor portfolios, identify and predict risky behavior, propose controls, automate workflows, collaborate with Product/Engineering/Data Science, and educate users to minimize losses while enabling growth.

Lead analytics projects using advanced and predictive modeling to optimize programs, forecast behavior, and drive revenue. Partner consultatively with business, IT, and SMEs across project lifecycle—intake through delivery—communicating results to stakeholders and senior leadership. Work independently on complex technical approaches and influence department strategy.

Partner with stakeholders to gather requirements, validate integrated datasets, and deliver trusted insights via SQL-driven analysis and Tableau/Qlik dashboards to support federal healthcare operational decisions.

Design, build, and maintain cloud-native data pipelines (Ingest→Transform→Expose) using Airflow, Spark, dbt, and Iceberg. Ingest and normalize HL7/FHIR/OMOP and other structured/unstructured data for analytics and AI, implement schema versioning and governance, ensure interoperability and compliance with DoD Responsible AI and NIST frameworks, and collaborate with DevSecOps and Data Science teams to deliver production-ready datasets.

Design, implement, and maintain dbt/Snowflake ELT transformations to convert raw clinical and multimodal health data into trusted, analysis-ready models; enforce data quality, lineage, testing, CI/CD, and documentation; collaborate with clinical and ML teams to harmonize ontologies and support de-identification and ETL across health systems.

Design, develop, and maintain enterprise Power BI reports, dashboards, and semantic models for healthcare, finance, and operations. Build complex DAX measures, optimize performance, administer Power BI Service (security, refreshes, gateways, deployment), establish governance, and collaborate with stakeholders to translate requirements into actionable analytics.

Support data migration projects by preparing, validating, transforming, and testing data. Validate field mappings, run SQL queries, perform data quality checks and reconciliations, document processes and findings, and assist cross-functional teams and clients under senior guidance.

Collect, clean, and validate data from multiple sources; analyze datasets to identify trends and KPIs; develop and maintain SQL queries and Excel workbooks; create visualizations; present findings to non-technical stakeholders; collaborate with business partners to translate requirements into data-driven recommendations and support the finance analytics ecosystem.

Support data migration projects by preparing, validating, mapping, transforming, and testing data. Use SQL and data tools to perform quality checks, reconciliation, and troubleshooting. Collaborate with Engineering, Implementation, and Client Success teams, document processes and findings, and assist client migration activities under senior guidance.

Lead and grow a data engineering team, set technical standards and roadmap, architect scalable GCP data solutions (ingest, transform, warehouse, serving), ensure pipeline reliability and data quality, partner with analytics and client teams, drive best practices (CI/CD, IaC, governance), and evaluate new tooling.

Work with the data team to design, build, and maintain scalable ETL pipelines and data models using Microsoft Fabric, dbt, PySpark, and SQL. Integrate and validate data across layers, optimize performance in Azure, follow GitHub CI/CD workflows, and document data governance while collaborating with cross-functional stakeholders.

Design and build a medallion architecture using dbt and Microsoft Fabric, create and maintain data ingestion pipelines, and implement governance, lineage, documentation, and quality checks to support self-serve analytics while collaborating with cross-functional teams.