Top Senior Data & Analytics Jobs in Providence, RI

The Staff Data Engineer will enhance the data ecosystem at WeightWatchers by developing data pipelines, collaborating cross-functionally, and ensuring data quality while leading projects and technical initiatives.

The Senior Data Scientist will lead innovative data science efforts, leveraging advanced analytics, visualization, and insights from complex datasets to boost productivity.

Design, build, and maintain data integration, warehouse, and BI solutions supporting subscriber acquisition, campaign and storefront systems. Create schemas, stored procedures, dashboards, and reports; optimize queries; aggregate multi-source data; ensure data quality, PII compliance, and platform observability. Collaborate across teams, mentor engineers, and provide executive reporting and analytics for video/OTT products.

The Sr. Data Engineer - Databricks designs and maintains scalable data solutions using Apache Spark and Databricks, ensuring data quality and performance for analytics and reporting.

Design and deliver scalable Power BI data models, dashboards, and reporting solutions. Collaborate with stakeholders, establish visualization governance and best practices, prototype solutions, and own projects end-to-end to enable data-driven decisions across healthcare teams.

The Senior Data Analyst will analyze performance data, identify trends, and provide insights to improve organic search performance for clients, working closely with cross-functional teams.

The Staff Data Analyst will enhance data usage for strategic decisions, architect scalable models, partner across teams on data solutions, and lead analytics engineering standards.

Design and implement data infrastructure and pipelines, ensuring reliability and quality. Collaborate with teams for data solutions and optimize processes. Coach junior engineers.

Analyze product and user engagement data to generate insights, build dashboards and reports, design and evaluate A/B tests, define success metrics with product and engineering, ensure data accuracy, and communicate findings to cross-functional stakeholders to guide product and business strategy.

Build and maintain automated ETL/ELT data pipelines, improve data quality and monitoring, optimize Postgres and BigQuery schemas and queries, develop internal tooling, support data governance (HIPAA), participate in on-call rotation, and collaborate across engineering teams to scale data systems.