Top Senior Data & Analytics Jobs in Columbus, OH

Manage CVS Health's data partnerships and monetization strategy, source new partnerships, ensure operational success, and drive data product adoption across analytics teams.

The job involves building responsive web dashboards, advanced data visualizations, and analytics tools for unmanned aircraft systems, requiring a deep understanding of UI/UX design and data presentation.

Lead the Decision Science function, designing ML models, overseeing experimentation frameworks, and ensuring model adoption across the company, driving operational and commercial improvements.

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.

Partner with customers and sales to design and present scalable Databricks Lakehouse architectures, build reference architectures and demos, consult on big data, ETL, and ML projects, validate integrations, and drive technical wins and adoption across accounts.

The Senior Data Analyst transforms data into insights to guide business decisions, conducts analyses, and improves data collection systems.

The Data and Reporting Architect will lead the design of data architectures and reporting systems, addressing complex data challenges and ensuring compliance with regulatory standards. Responsibilities include mentoring engineers, defining data quality frameworks, and collaborating with various teams to implement scalable solutions.

The Senior Product Analyst will lead product analytics, design A/B tests, build dashboards, and integrate customer insights to drive product strategy and improve customer experience.

The Senior BI Analytics Engineer will design and deliver data models for analytics, ensuring data quality, and collaborating across teams to enhance AI-driven reporting and querying capabilities.

Lead design, build, and maintain scalable data pipelines and infrastructure using Azure Databricks, ADF, and SQL Server. Develop OLTP and dimensional models, integrate Salesforce and SaaS sources, implement batch and real-time processing, enforce data governance and CI/CD, troubleshoot performance, mentor team members, and drive improvements to reduce technical debt and improve cost and performance.