Top Analysis Reporting Jobs in Providence, RI

Design, build, and maintain scalable ELT data pipelines and models to power reporting, analytics, and operational workflows. Troubleshoot data quality and performance, participate in incident response, support CI/CD deployments, collaborate with cross-functional teams, and contribute to data platform modernization and engineering best practices.

Lead architecture and implementation of cloud-native data platforms on Google Cloud (BigQuery). Build unified batch/streaming pipelines, enforce IaC with Terraform, implement open table formats and governance (Dataplex/Data Catalog), automate data quality/lineage, partner with analytics and product teams, and mentor data engineers.

Analyze complex datasets to detect and prevent fraud, build dashboards, optimize queries, and collaborate with cross-functional teams in risk management.

Lead data conversion processes, provide expert guidance on Oracle Cloud, and ensure the successful implementation of conversion solutions while collaborating with stakeholders.

Lead the implementation and support of Oracle HCM solutions, focusing on integrations and conversions. Collaborate with teams, resolve issues, and provide training. Ensure integrations function smoothly and meet project requirements.

As a Principal Data Engineer, you will design and implement data infrastructure and solutions, collaborating across teams to enhance healthcare data usage.

Lead the vision and execution of a scalable, multi-tenant data platform: own ingestion, warehouse, transformation, BI, and AI-on-data layers. Manage and grow a data engineering team, define engineering standards (CI/CD, infra-as-code, testing, lineage), productize integrations, and collaborate with Product, Engineering, and GTM for client onboarding and data delivery.

Build reliable data models and semantic layer for AI-powered analyses. Support Product, Finance, and Customer Success with SQL-based analytics, BI dashboards, and stakeholder storytelling. Standardize data team processes, prioritize work, and collaborate across company to enable data-informed decisions.

Partner with Sales, RevOps, Marketing, and Customer Success to connect the full revenue funnel. Produce GTM insights using advanced analytics, SQL, and BI tools; communicate findings to stakeholders; standardize Data team processes; mentor analysts and lead data-driven initiatives to drive business outcomes.

Design and advance enterprise data and BI architecture: optimize OLTP/OLAP models, establish modeling/integration/governance standards, lead POCs, mentor teams, enable AI/ML, and guide cross-functional implementation from concept to production.

Embed within a core business area to define problems, build metrics/reports, run analyses and experiments, surface insights, and drive recommendations to deliver measurable business outcomes across growth, product, AI, and partnerships.

Embedded on a core business team, own analytics end-to-end: define problems, build reports and experiments, analyze data, surface insights, and drive recommendations that influence product, growth, AI/automation, or partnership decisions.

Embed with a core business unit to define problems, build metrics, run analyses, design experiments, surface insights, and drive data-informed decisions end-to-end across growth, product, AI, or partnerships.

Own analytics for an embedded business unit: define problems and metrics, build reports, run analyses, design experiments, and drive cross-functional recommendations to improve growth, product, AI, or partnerships.

Embed with a core business area to define problems, build metrics and reports, run analyses and experiments, surface insights, and drive recommendations to execution across growth, product, AI, or partnerships.

Embed with a core business unit to define problems, build metrics/reports, run analyses and experiments, and drive data-informed recommendations end-to-end to improve product, growth, AI, or partnerships.