Top Data & Analytics Jobs in Cincinnati, OH

Manages a data engineering team responsible for scalable, reliable data pipelines, infrastructure, and analytics tooling. Provides mentorship, performance management, and technical leadership while coordinating with product, analytics, finance, compliance, engineering, and regulators. Prioritizes cross-functional projects, supports data architecture and governance, ensures performance and reliability, and operates within strict regulatory and audit requirements.

Own the company’s data function by designing and optimizing Snowflake architecture, pipelines, integrations, data models, BI dashboards, metric definitions, governance, and data-quality standards. Partner with leadership and cross-functional teams to translate operational needs into trusted data products. Automate recurring reporting, troubleshoot ingestion issues, perform ad hoc analysis, and establish scalable analytics practices as the first dedicated analytics hire.

Owns enterprise workforce intelligence and employee listening strategy. Analyzes employee sentiment, workforce trends, talent, skills, organizational effectiveness, and work data to identify risks and opportunities. Develops dashboards, analytical methodologies, AI-enabled insight products, and self-service resources. Partners with HR leaders and data owners to translate complex quantitative and qualitative findings into actionable recommendations for workforce planning, succession, organization design, automation, and capability decisions.

Design, develop, and publish advanced interactive Power BI reports and dashboards; define data structures and ETL needs; build analytics models using Microsoft BI stack (Power BI, SSAS/AAS, dataflows); use DAX and SQL to implement complex logic; collaborate with data engineering and business partners; mentor junior developers and performance-tune reports.

Supports loyalty and retention analytics through A/B test management, KPI tracking, recurring dashboards, and performance reporting. Monitors churn, winback, cancellation, and loyalty metrics; identifies trends, risks, and opportunities; and translates findings into actionable recommendations. The role also manages loyalty merchandise planning and replenishment, collaborates with Data Science and program owners, coordinates analytics requests, and prepares MBR/QBR materials.

Own sales analytics and forecasting as the trusted source of truth for sales leadership. Build predictive and machine learning models to assess deal close likelihood and slippage, maintain Salesforce and Tableau dashboards, improve data governance, and translate complex business questions into actionable GTM recommendations. Partner with Sales, Marketing, and Finance on reporting standards, strategic planning, QBRs, and executive insights.

Analyzes retail measurement, consumer, and shopper data to answer client business questions, develop category insights, visualize findings, and present compelling stories. The role supports client briefings, ad hoc analysis, category performance reviews, thought leadership projects, and lead generation while learning NIQ tools, metrics, and service standards.

Supports leadership by analyzing business processes, systems, technologies, and operational data to identify improvements. Administers and configures business platforms, provides second-level technical support, conducts system audits, develops reports, validates data, and evaluates workflows. The role advises cross-functional teams, leads improvement initiatives, mentors junior staff, and manages operational adjustments while using statistical and trend analysis to support performance decisions.

Lead enterprise data architecture across AWS and Databricks Lakehouse: design scalable data models, ensure governance and data quality, mentor teams, evaluate and adopt data technologies (Delta Lake, Unity Catalog), oversee large projects and deliverables, and incorporate generative AI to accelerate data modeling and delivery.

Design, maintain, and automate GTM business data models, ensure data quality and observability, build BI-as-code pipelines (CI/CD, Git), create visualizations, and partner with Sales, Marketing, Finance, and Product to enable reliable reporting, analytics, and AI capabilities.