Top Senior Data & Analytics Jobs in Dayton, OH

Lead people-analytics strategy for Talent Acquisition and Talent Development. Drive end-to-end analysis of complex workforce problems, deliver evidence-based recommendations to senior leaders, ensure data governance and quality, coach junior analysts, build metrics frameworks, and conduct benchmarking and external research to inform workforce strategy.

Responsible for designing, developing, and maintaining scalable data pipelines and infrastructure, implementing data governance, and collaborating with teams to meet data needs.

The Director of Data Analytics & Business Intelligence leads analytics functions, building models and dashboards while guiding a team. Responsibilities include analytics infrastructure management, cross-functional collaboration, and driving AI/ML initiatives.

Lead measurement strategy for a book of clients, designing statistical models (MMM), experiments (MMT), and customer analyses. Use R, Python, SQL and ETL tools to extract insights, present advanced methodologies to stakeholders, provide strategic recommendations tied to business goals, mentor measurement analysts, drive process efficiencies, and leverage proprietary Nova tools and AI to optimize deliverables.

Lead design, development, and migration of enterprise data warehouse solutions from SAP BW/BW4HANA to SAP Datasphere. Architect data models and hybrid data flows with Microsoft Fabric/Azure Synapse, integrate BW with Salesforce and SQL Server, embed AI capabilities (Copilot, Azure OpenAI), manage offshore teams, enforce standards, and deliver Power BI reporting and analytics to business stakeholders.

Lead design, development, and migration of enterprise SAP BW solutions to SAP Datasphere; architect hybrid data flows with Microsoft Fabric and Azure Synapse; integrate BW with Salesforce and SQL Server; embed AI (Copilot, Azure OpenAI) into analytics; manage deliverables, mentor offshore teams, enforce standards, and ensure data integrity and performance for reporting and analytics.

Lead design and scaling of ELT pipelines and analytics schemas on Snowflake. Build Looker views, CI/CD automation, and orchestration workflows (Prefect/Airflow). Ensure production reliability with monitoring (Datadog, Monte Carlo), partner with cross-functional teams, and provide technical leadership including code reviews, testing, and end-to-end ownership of data integrity and platform trustworthiness.

Design and govern conceptual, logical, and physical enterprise data models supporting analytics, reporting, AI-ready datasets, and certified data products. Translate business requirements into scalable data structures across customer, product, payer, and territory domains. Establish modeling standards, review models against Common Data Model standards, maintain metadata and lineage accuracy, and resolve data gaps and inconsistencies. Collaborate with business, engineering, and technology stakeholders to provide modeling expertise and design guidance.

Leads and develops a data engineering team implementing data integrations for partner campuses. Owns implementation approaches, scalable delivery processes, data mapping, validation, reconciliation, quality controls, project health, and capacity planning. Partners with Product, Launch, and Partner Success teams to resolve technical and partner challenges, improve integrations, and support adoption. Provides technical mentorship, design and code reviews, stakeholder communication, and continuous process improvement.

Develop Power BI dashboards, reports, data models, and analytical tools for federal consulting engagements. Gather stakeholder requirements, integrate and validate operational data, create DAX calculations and Power Query transformations, and support forecasting, staffing, cost, inventory, and performance analysis. Optimize and document solutions, conduct testing and training, and transfer knowledge to Government users. Collaborate with logistics, operations research, security, and project management stakeholders.