Top Data & Analytics Jobs in Cincinnati, OH

Leads the design and implementation of AI-powered data pipelines, enterprise feature stores, analytics-ready repositories, and self-service data access layers. Builds automated feature engineering, data quality, observability, and governance capabilities for large-scale data science workloads. Partners with Enterprise IT, establishes data availability and quality SLAs, integrates structured and unstructured data sources, and leads teams delivering scalable analytics infrastructure.

Build and extend automated enterprise data governance and quality frameworks. Define measurable trust rules, data contracts, validation and certification workflows, metadata, lineage, tagging, and trust scoring across a cloud data platform. Integrate governance checks into developer workflows and Collibra, coach engineering and product teams, and establish organization-wide data trust standards. The role requires strong SQL, BigQuery or comparable warehouse experience, and expertise with data quality or observability tools.

Build and maintain dbt analytics models using SQL and Jinja, implement data quality tests and freshness checks, create Metabase dashboards, perform ad hoc analysis, and collaborate with finance, product, sales, and customer success stakeholders. The role requires advanced SQL, data modeling, analytics engineering, documentation, statistical analysis, Git-based development, and CI/CD experience, with Snowflake, Python, and data analysis tools preferred.

Analyzes, cleanses, validates, and prepares operational datasets for mailing, email, reporting, billing, and processing activities. Develops Databricks queries and Alteryx workflows to automate processes and improve data quality. Performs audits, reconciliations, root-cause analysis, and corrective actions while maintaining governance and security compliance. Provides actionable insights, mentors junior analysts, communicates findings, and leads continuous improvement initiatives.

Leads analytics for SEO, AI search, website experience, CRO, and the organic enrollment funnel. Diagnoses performance across traffic, visibility, conversions, leads, applications, and enrollments; designs measurement approaches; reconciles web, search, CRM, and platform data; defines KPI and reporting requirements; and translates findings into executive recommendations. Partners with analytics and engineering teams to build scalable Databricks-based reporting and improve measurement of organic and AEO initiatives.

Develops credit strategy analysis, portfolio reporting, dashboards, and predictive insights using large datasets. Builds and automates Power BI reporting solutions, identifies credit risk trends, translates business needs into technical specifications, and delivers recommendations to improve credit policy and strategy. Provides analytics consulting, documents processes, supports self-service reporting, and trains non-analytical users. Requires collaboration with stakeholders and independent problem-solving in a banking environment.

Design, build, and maintain scalable batch and streaming data pipelines, cloud infrastructure, and the Enterprise Data Hub. Partner with stakeholders to productionize ingestions, ensure data quality, implement metadata/catalog solutions, mentor junior engineers, and support analytics and ML workloads using cloud and big-data tooling.

Analyze platform, product, customer, advertising, and operational data to generate actionable insights. Build dashboards, reporting frameworks, automated workflows, and scalable analytics pipelines. Evaluate experiments and analytical methodologies, improve forecasting and data accuracy, and partner with product, engineering, marketing, revenue, and leadership teams to influence strategy, customer experience, and platform growth.

Analyzes consumer, shopper, and market data to identify trends, risks, and growth opportunities. Translates complex findings into presentations, visualizations, recommendations, and client-ready insights. Supports client meetings, cross-functional solution development, relationship building, and engagement expansion while developing expertise in Circana’s data assets and platforms.

Lead data engineering initiatives that build scalable warehouses, pipelines, ETL/ELT processes, dashboards, and automated reporting workflows. Translate finance and operational needs into reliable data solutions, implement governance and quality practices, and support integrations, migrations, acquisitions, and system enhancements across portfolio companies. Partner directly with finance, accounting, analytics, and operational stakeholders to improve decision-making.