Top Senior Data & Analytics Jobs in Providence, RI

Design, build, and optimize BigQuery-based data solutions and data models. Manage data storage, partitioning, clustering, ETL, and data quality. Collaborate with architects, data scientists, and engineers to deliver scalable, secure cloud data infrastructure and documentation; senior hires provide technical leadership, code review, and process improvement.

Partner with People teams to turn HR and org data into actionable insights. Build complex queries, statistical analyses, dashboards, and a centralized people data repository. Drive data governance, data quality, and stakeholder communication to support hiring, retention, productivity, and workforce decision-making.

The Data Analyst in Revenue Operations will analyze sales data, build models, and create reports using SQL, Excel, and BI tools to empower business decisions.

This role drives data-driven decision-making in product analytics, collaborating with cross-functional teams to generate actionable insights and evaluate new launches to enhance platform growth.

Design, implement, and validate data mapping, transformation, and integration solutions for payment integrity. Investigate and resolve complex data quality issues, create mapping specs and documentation, partner with stakeholders, and mentor analysts to improve data quality and automation.

Owner of the analytics foundation: design and maintain BigQuery/dbt models, pipelines, and Looker Studio reporting; build AI workflows and web apps on GCP; integrate marketing, e-commerce, and fulfillment data; ensure GCP ops, security, and reliability; use AI-assisted tools daily and collaborate with business and client stakeholders.

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 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 the enterprise data platform strategy and architecture, driving Snowflake/dbt-based platform evolution, self-service Data Mesh and medallion models. Build AI-ready pipelines, RAG systems, and observability/cost frameworks while managing a central data team, supporting federated BI, and executing hands-on technical work.

The analyst will own planning for launches, build forecasting models, partner with stakeholders, and drive data-driven decisions using AI and analytics.