Top Analysis Reporting Jobs in Cincinnati, OH

Conduct test-versus-control analyses for in-store media campaigns, query point-of-sale data with SQL, and identify campaign performance drivers. Build reports and dashboards in support of sales and client-facing teams, translate quantitative findings into actionable recommendations, and collaborate on data integration and process improvements. The role requires strong communication, organization, and analytical skills, with retail, CPG, merchandising, promotional, or marketing analytics experience preferred.

Build and operate governed data pipelines using Microsoft Fabric, Azure, Python, PySpark, Spark, and SQL. Implement Medallion Architecture, ingest data from APIs and enterprise systems, and develop lakehouse and Azure SQL data products supporting analytics and AI. Use Git and CI/CD for deployments, explore AI agentic workloads, and partner with architects and stakeholders to translate requirements into scalable solutions. The role requires local travel, occasional overtime and weekends, and in-person work flexibility.

Uses consumer and shopper analytics to support business strategy, uncover growth opportunities, and influence decisions. The role partners with Brand Management, Finance, Sales, R&D, and other functions, combining diverse data sources with human insights to deliver actionable recommendations. Responsibilities include communicating across teams, solving business problems, delivering real-time insights, and driving data-informed actions. Candidates need a relevant bachelor's degree, strong analytical and communication skills, creativity, initiative, and willingness to relocate.

Executes brand lift studies for Reddit media campaigns from setup through reporting and presentation. Responsibilities include leading client kickoffs, designing surveys, analyzing data, preparing recommendations and final reports, conducting quality checks, managing timelines, collaborating with sales and measurement teams, and improving processes. The role requires strong communication, organization, client relationship skills, digital advertising knowledge, and familiarity with experimentation and statistical methods.

Designs and builds scalable data platforms and pipelines for scientific, clinical, manufacturing, and process-engineering data. Responsibilities include developing batch and streaming ETL/ELT systems, integrating Databricks, Snowflake, cloud platforms, MES, SCADA, and laboratory systems, and enforcing governance and GxP compliance. The role provides hands-on technical leadership, establishes data engineering standards, and collaborates with scientists, process engineers, and platform teams. It requires three days onsite weekly in Indianapolis and unrestricted U.S. work authorization.

Leads business intelligence and advanced SQL analytics using Snowflake, Tableau, Power BI, and Python. Analyzes complex data, validates data integrity, develops semantic models and reporting solutions, partners with stakeholders and IT data teams, presents insights, improves analytics processes, documents standards, and mentors analysts. The role requires strong business judgment, communication, governance, and technical leadership.

Leads geospatial and GIS projects using the Esri platform to create maps, dashboards, spatial analyses, and field data solutions. Manages spatial data quality, project budgets, timelines, client relationships, proposals, and multidisciplinary deliverables. Advises clients on geospatial technologies and serves as a GIS project lead while supporting environmental assessments, infrastructure, permitting, and resource-planning projects.

Collect, analyze, and interpret complex datasets to create and maintain customer-facing Tableau reports; collaborate with customer services and development teams to scope reports and data models; investigate data accuracy issues and communicate insights to stakeholders.

The Sr. IT Business Analyst will support digital/mobile projects by analyzing business requirements, leading teams, assisting in testing, and fostering Agile Scrum methodology.

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