Top Remote Data & Analytics Jobs in Providence, RI

Deliver sales reporting, data preparation, dashboard updates, and analysis to support sales intelligence. Maintain data accuracy across the warehouse and CRM, build Power BI visuals, execute ETL processes, and translate insights for non-technical stakeholders.

Design and implement enterprise analytics tracking across web, mobile, and SPAs using Tealium and other TMSs. Maintain data layers and SDRs, configure tags and events, validate data integrity, collaborate with engineering teams, mentor junior staff, produce technical documentation, and support presales and thought leadership activities.

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.

Lead and grow a data engineering team that builds and operates ingestion, transformation, orchestration, and serving layers and a self-serve analytics substrate. Own data quality, observability, cost efficiency, SLAs, and engineering practices while partnering with Data Science, BIE, Analytics, and Product to deliver reliable, reusable data products.

Lead and grow a team of analytics engineers while remaining hands-on with SQL, dbt, and Snowflake. Own roadmap and semantic layer development, build trusted, governed data products, partner with cross-functional stakeholders, champion data quality and observability, and hire and coach engineering talent to deliver scalable analytics and AI-ready foundations.

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.

The Senior Data Analyst oversees performance reporting tools, automates data pipelines, conducts quantitative analyses, and communicates findings to various stakeholders.

Lead statistical analysis for clinical studies in oncology and cardiology, provide project leadership, and mentor junior biostatisticians while ensuring regulatory compliance.

Build and scale the analytics foundation: own dbt projects and Snowflake warehouse, create trusted datasets and semantic layers for AI, build ELT pipelines from APIs, implement testing/observability and CI/CD, design reconciliation models, enable stakeholder self-service, and partner cross-functionally to drive data-driven decisions across GTM, Product, Finance, People, and Operations.

Build, deploy, and operate production-grade data pipelines and data products for healthcare audiences. Design transformations, data models, and governed views using Python, SQL, Airflow, S3, Snowflake, and EMR. Implement data-quality, monitoring, and privacy-by-design controls for PHI/PII. Partner with product, analytics, and platform teams to onboard sources, support audience discovery, segmentation, activation, measurement, and troubleshoot production issues.