Top Senior Data & Analytics Jobs in Columbus, OH

The Senior Data Engineer will architect, build, and maintain scalable data pipelines and infrastructure, mentor junior engineers, and collaborate on data solutions for Openly's insurance platform.

The Senior Data Engineer will own and evolve data pipelines, collaborate with teams for data models and pipelines, optimize ETL processes, and implement data storage solutions.

The role involves assessing fraud program effectiveness, compliance with regulations, and providing strategic insights for risk management within the financial services industry.

Lead design and implementation of scalable, HIPAA-compliant data pipelines and platforms for healthcare ML. Build ETL, orchestration, and tooling for processing EHR, claims, pharmacy, and bioinformatics data; collaborate with data scientists to produce modeling-ready datasets and ensure data quality, reliability, and operational excellence.

The Senior Analyst will support the personalization algorithm by conducting analyses, testing features, managing projects, and collaborating with teams to improve food recommendations for customers.

The Strategist III, Value Analytics will own strategic workstreams, revamp dashboards for billing data, conduct analyses, and lead independent projects, improving Cedar's reporting suite.

The Analytics Manager will lead a team of analysts, focusing on data product delivery in the life insurance sector, while ensuring quality standards and mentoring team members.

Lead client engagements delivering advanced reporting, analytics, and large-scale historical data migrations into Unanet ERP AE. Design and validate complex SQL, SSRS, and Power BI solutions, mentor junior consultants, use AI-assisted tools for analysis and QA, and manage multiple projects to ensure accurate reconciliation and client outcomes.

The Revenue Analytics Manager will analyze customer success and partner analytics, delivering insights to drive retention and revenue growth, working cross functionally with leadership and data teams.

Lead detection, investigation, and mitigation of payments fraud across cards and mobile. Build and own risk controls, metrics, reporting, and cross-functional analytics projects using SQL and BI tools to scale monitoring and partner with product, data science, and engineering.