Top Analysis Reporting Jobs in Dayton, OH

The Data Engineering Lead will guide a team to build a scalable AI-ready data platform, focusing on data governance, pipeline reliability, and mentoring engineers to enhance data accessibility and usability.

The Analytics Manager analyzes complex datasets, builds models, conducts scenario analyses, and provides strategic recommendations to guide decision-making for leadership.

The Senior Manager, Commercial Forecasting and Insights leads global forecasting, analytics, and insights to drive revenue performance through strategic partnerships with sales and finance leadership.

The Principal Data Engineer will lead data architecture initiatives, design scalable data systems, and oversee data standards across teams while ensuring high-quality data infrastructure and guiding engineering teams.

Design and execute SQL-based ETL processes to migrate legacy public safety data into Mark43. Collaborate with customers, contractors, and internal teams to map legacy schemas, handle edge cases, ensure data fidelity, and improve migration tooling while managing timelines and stakeholder relationships.

We are seeking an experienced data analyst to maximize our service offerings through data mining, generation, and visualization, while producing goal-oriented reports.

As a Machine Learning Engineer, you'll develop and deploy ML models for medical imaging, collaborate with teams, and optimize for production environments.

Lead enterprise data, analytics, and AI transformation engagements as a strategic advisor and architect. Design cloud data platforms, warehouses/lakehouses, governance, integration, and BI solutions. Oversee delivery, establish standards, mentor teams, support presales, and drive measurable business outcomes across technologies like Oracle, Snowflake, Databricks, and Microsoft Fabric.

As a Data Engineering Architect, lead the transformation of data engineering into a modern platform, oversee architecture and technical leadership, design scalable systems, ensure data quality and governance, and mentor teams for a data-driven culture.

Design, build, and maintain data lakes, data warehouses, and end-to-end data pipelines for a multi-tenant SaaS platform. Lead code and design reviews, write infrastructure-as-code, optimize performance and scalability, participate in data governance, mentor junior engineers, evaluate new technologies, automate tests, collaborate cross-functionally, and join on-call rotation to ensure reliable data delivery.