Top Business Intelligence Jobs in Cincinnati, OH

Lead design and build of ETL pipelines and Gold Layer tables in Databricks; develop semantic layers, data dictionaries, and AI-ready documentation; create dashboards and ad-hoc analyses to surface marketing and sales KPIs; partner with stakeholders to translate requirements into analytics-ready datasets and enable self-serve BI and agentic AI workflows.

Lead and expand the enterprise reporting and BI platform: gather requirements, develop reports and visualizations, write complex T-SQL/stored procedures, ensure SDLC practices, mentor junior developers, and partner with stakeholders to deliver accurate, timely business insights.

The Senior Data Analyst oversees performance reporting tools, automates data pipelines, conducts quantitative analyses, and communicates findings to various stakeholders.

The Cloud Data Engineer will design and develop data warehouse solutions, create efficient data pipelines, collaborate with teams, and monitor system health.

The Senior Business Intelligence Analyst analyzes complex data, ensures accuracy, develops reports, and enhances analytics processes while collaborating with cross-functional teams.

The BI Consultant will design analytic solutions, build dashboards using Power BI/Tableau, perform data analysis, and provide strategic insights for clients.

Founding sales-intelligence analyst building data models, scoring/prioritizing account opportunities, packaging analysis for non-technical stakeholders, presenting to sales leadership, and iterating with sales and operations to drive pipeline growth.

Lead the BI function—manage BI engineers, analysts, and PMs; develop strategic BI vision and data roadmap; oversee data modeling, transformation, visualization, governance, QA, and stakeholder engagement to move reporting toward analytical and predictive insights.

The Power BI Data Analyst will create actionable dashboards from large datasets, optimize performance, collaborate with business teams, and mentor junior analysts.

The Business Intelligence Architect will design Circana Brainwaves to transform data into actionable insights, engaging stakeholders and ensuring solutions align with client needs.

The Director of Business Intelligence at Viral Nation will lead analytics strategy for a CPG organization, driving insights and growth opportunities across sales, marketing, and digital engagement. Responsibilities include building a high-performing team, developing predictive models, and optimizing measurement strategies to inform executive decisions.

Design, develop, and maintain Power BI dashboards and automated reports for financial analytics. Ensure data accuracy, build data models and ETL pipelines, write/optimize SQL and DAX, analyze trends to provide insights, and collaborate with stakeholders to define reporting requirements and best practices.

The Senior BI Analyst will gather requirements, develop scalable reporting solutions, and create dashboards using Power BI, ensuring data-driven decisions across the organization.

The Data & Accounting Analyst will analyze financial and marketing data, create detailed reports, and ensure accuracy in financial data to support strategic decisions.

The Director of Data and Enterprise Applications oversees the architecture, development, and support of business applications and data platforms, driving digital transformation and ensuring data integrity and accessibility.

Work with operations, IT, and client teams to manage business applications, schedules, SFTP accounts, and automated reports. Perform data imports/exports, cleansing, QA reporting, trend analysis, and process improvements while maintaining client communication and meeting productivity goals.

Lead and grow a BI and analytics team to build scalable, AI-enabled reporting and self-service analytics. Partner with cross-functional stakeholders to deliver executive dashboards, standardize metrics, ensure data quality and governance, and use AI tools to automate insights and accelerate dashboard development.

Design, build, and maintain scalable AWS data pipelines, data lakes, and warehouses; develop ETL/ELT processes; create and manage AWS QuickSight dashboards (including RLS, embedding, Topics/Spaces, and QuickSight Q); ensure data quality, governance, security; optimize performance; collaborate with stakeholders and support production reporting.

Design, build, and maintain data pipelines, dashboards, and predictive models. Analyze large datasets to generate actionable insights, collaborate with stakeholders, ensure data quality and governance, and document/share analytics best practices to support Marketing, Product, Operations, and Workforce teams.

Designs and develops BI solutions by analyzing large datasets, building and optimizing SQL queries, and creating data visualizations (Power BI/Tableau) to inform strategic decisions. Works independently on complex problems, influences departmental strategy, and supports healthcare-focused analytics.

The Senior Business Intelligence Analyst will transform data into insights, design dashboards, and provide analytical support for strategic decisions, working closely with stakeholders and teams.

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.

Design, develop, and maintain enterprise Power BI dashboards and reports. Integrate data from SQL Server, Azure, Excel and other sources, perform data modeling and DAX calculations, validate data, and document data models and reporting logic while partnering with business stakeholders.

Embed as the primary product analytics partner on a digital product team. Define measurement plans, KPIs, funnels, build Power BI dashboards, analyze member behavior and funnel drop-off, design and interpret A/B tests, write SQL and Python for analysis and automation, and translate findings into clear product recommendations.

Architect and scale a governed BI and analytics platform (Snowflake, dbt, Sigma) to deliver trusted, standardized KPI frameworks and semantic layers. Build high-quality data models, optimize SQL for large datasets, enable self-serve analytics, mentor engineers, drive governance and testing standards, and partner with Product, Data Science, Finance, and business teams. Promote AI-assisted tooling to accelerate analytics delivery and improve metric trust and reporting consistency.