Top Senior Data & Analytics Jobs in Cincinnati, OH

Lead actuarial analyses for value-based care, forecasting Medicare risk and financial performance using large claims and EHR datasets (CCLF, BCDA). Build SQL data structures, IBNR and risk score projections, create executive dashboards, support budgeting, and ensure regulatory compliance under CMS/CMMI programs.

Hands-on technical lead designing and delivering scalable, secure Azure-based BI and analytics solutions. Own end-to-end Power BI architecture, mentor engineers, guide implementations, optimize performance, and advise clients on governance, deployment, and AI-augmented analytics. Drive discovery, backlog priorities, cross-team alignment, reusable assets, and consulting pursuits.

Lead design and governance of enterprise Master Data Management using Stibo/MDM platforms. Define canonical data models, integration patterns (API/event-driven), match & merge and survivorship strategies, stewardship workflows, data quality and lineage, RBAC, and scale multi-domain MDM across Product, Customer, and Supplier domains while aligning with enterprise data governance and cloud platforms.

Lead analytics strategy for client accounts: create measurement plans, testing roadmaps, and cross-channel analyses. Use BI tools and SQL to connect data, generate insights, and present clear, actionable recommendations to clients and internal teams.

The Senior Data Engineer will maintain and improve data infrastructure, design ETL processes, and create high-performance pipelines for analytics and AI initiatives using SQL and Python in cloud environments.

Serve as a senior advisor on enterprise data architecture and Adobe Experience Platform. Lead client discovery, design XDM schemas and identity resolution, guide data ingestion/ETL, governance, and Customer 360 initiatives. Provide technical leadership, mentor teams, review architecture, and contribute templates and best practices across consulting engagements.

Build and maintain scalable ETL/data pipelines and internal frameworks to support ML and product teams. Drive architecture, observability, data quality, and engineering best practices across AI/ML workflows and prompt-engineering pipelines.

Build governed gold-layer data models and a single-source metrics layer in Snowflake (dbt); create and optimize dashboards in enterprise BI tools; use AI coding agents and AI-assisted tooling to accelerate development; ensure data quality, governance, and consistency; collaborate with data engineering and stakeholders to deliver trusted analytics for internal and client-facing use.

Client-facing BI consultant responsible for end-to-end delivery of TARGIT-based analytics: requirements gathering, prototyping, backend work, dashboards, training, deployment, optimization, and customer engagement.

Lead enterprise data strategy and governance, build AI-ready data infrastructure and BI systems, own SharePoint platform, partner cross-functionally to ensure data quality, access, compliance, and user adoption.