Top Data & Analytics Jobs in Dayton, OH

Leads data engineering for LillyDirect’s patient analytics platform, designing privacy-first ingestion pipelines, tokenization, identity resolution, consent governance, semantic layers, and analytics-ready data products. Integrates pharmacy and prescription data across enterprise systems while ensuring HIPAA compliance, data quality, governed access, and consent revocation. Partners with product, pharmacy, privacy, legal, cybersecurity, and analytics teams to translate requirements into scalable solutions supporting BI, reporting, self-service analytics, and agentic AI.

Own and improve high-impact data products, ingestion pipelines, and granular data feeds. Analyze large datasets to answer client and stakeholder questions, ensure data accuracy, and derive insights. Collaborate with clients and internal teams, develop new methodologies and features, and scale third-party datasets. The role includes training in SQL, PySpark, Python, and internal tools.

Lead data analysis for product and customer decision-making by defining metrics, measuring adoption, engagement, retention, and customer health, and translating complex data into actionable insights. Partner with product, engineering, customer success, and sales teams; automate and improve data processes; support product strategy and customer reviews; strengthen data governance; and mentor analysts.

Lead and develop Analytics Engineers responsible for shared data foundations, platform capabilities, semantic models, developer tooling, and AI-enabled workflows. Define the team vision, operating model, roadmap, standards, and success measures. Partner cross-functionally to prioritize initiatives, improve adoption, guide architecture, and deliver scalable data assets and automation. Drive responsible AI-assisted development, data reliability, testing, documentation, observability, and cost management while contributing hands-on when needed.

Leads enterprise data engineering and platform execution, including modernization roadmaps, cloud transformation, governance, reliability, operational excellence, budgets, vendors, and investment prioritization. Directs multiple engineering managers and teams across platform engineering, data engineering, integration, and operations. Partners with architecture, security, compliance, analytics, clinical, product, finance, and business leaders to deliver secure, scalable, resilient data capabilities supporting AI, interoperability, reporting, and digital transformation.

Analyzes property claims data, defines BI strategies, and delivers executive and operational dashboards. Partners with business and technical teams to gather requirements, source and validate data, support integrations, conduct UAT, manage reporting access, investigate data issues, and provide actionable insights and recommendations. The role also supports reporting platforms, trains users, and communicates system and process changes.

Designs, develops, tests, deploys, and maintains Power BI dashboards, reports, dataflows, and semantic models. Engineers Dataverse connections, develops DAX calculations, transforms data with Power Query M, and implements security, governance, version control, lifecycle management, and workspace organization. Partners with stakeholders to translate reporting requirements into technical solutions, engages customers, and trains data analysts. Requires four years of Power BI development and data engineering scripting experience, plus Secret clearance or higher.

Design, build, and maintain data pipelines, ingestion and transformation workflows, SQL-based processes, data models, and cloud data infrastructure for a B2B SaaS analytics platform. Monitor pipeline performance and data quality, troubleshoot failures, document data architecture and business logic, and collaborate with engineering, product, and analytics stakeholders.

Transforms complex retail and consumer data into business-ready datasets, scalable pipelines, reporting solutions, automation, and client deliverables. Designs data integration solutions in Unify, troubleshoots connector issues, explores AI-driven improvements, and partners with Product, Engineering, Client Development, Operations, and business stakeholders to define requirements and deliver scalable solutions.

Own client-facing analytics strategy and implementation across GA4, Adobe Analytics, tagging, measurement frameworks, dashboards, experimentation, and GEO measurement. Audit and QA analytics implementations, define KPIs, evaluate incrementality and causal relationships, present executive-ready insights, and collaborate with SEO, paid media, creative, data, engineering, and client teams. Build AI-assisted workflows, automations, scalable tools, and dashboards while mentoring teammates and managing multiple client workstreams.