Top Data & Analytics Jobs in Providence, RI

The Senior Analytics Engineer will design and build scalable data pipelines using dbt and Snowflake, providing technical guidance, conducting audits, and mentoring junior engineers while leveraging AI tools to enhance productivity.

Design, develop, and optimize Tableau dashboards and data sources on Redshift; collaborate with data engineering (dbt) and business teams; own Tableau governance, performance tuning, documentation, training, and ensure data security compliance.

The Junior Manual QA Engineer will execute test cases, perform exploratory testing, document bugs, and collaborate with teams to ensure high-quality software. This role involves learning QA methodologies and improving testing processes alongside experienced professionals.

Lead the Data Engineering team at Docker, focusing on strategic data analytics and platform evolution to enhance product innovation and customer insights.

The Senior Insurance Product Analyst will develop pricing models, analyze product profitability, and collaborate with teams on market strategies, utilizing AI tools for data-driven decisions.

The Business Analyst will gather, analyze, and document requirements for health IT solutions, support UAT, and collaborate with stakeholders to improve processes.

The Senior Business Analyst collaborates with stakeholders to optimize Oracle Fusion solutions for Supply Chain Management, focusing on Order Management and Procurement, ensuring process integration and functionality. Responsibilities include requirements gathering, configuration, testing, and supporting post-go-live improvements.

The Data Migration Engineer will design and execute SQL-based ETL processes for migrating public safety data, ensuring high-quality data integration and collaboration with internal and external teams.

The role involves project management, efficiency analysis, quality assurance, and systems management with a focus on improving operational workflows and processes.

Lead data architecture and strategy across product, data science, and engineering. Design cloud-centric, scalable data models, ETL/ingestion, governance, and AI/ML-ready analytics. Guide tooling selection, proofs-of-concept, data storage decisions, security/compliance, documentation, and mentor Data Platform team members to operationalize mission-critical data solutions.