Top Analysis Reporting Jobs in Dayton, OH

Architect and operate BILL’s enterprise data platform across ingestion, lake storage, batch and streaming processing, query, feature store, knowledge graph, and search layers. Drive platform-wide technical decisions, migrations, standards, reliability, cost efficiency, and self-service capabilities. Partner with ML, Risk, Payments, and Analytics teams to deliver scalable solutions, lead complex initiatives from inception through production, and mentor senior and staff engineers.

Own board-grade analytics deliverables for client engagements by transforming Salesforce pipeline data and BI outputs into executive narratives, presentations, and reusable reporting templates. Analyze pipeline, funnel, and revenue performance; explain variance; write causal commentary; present findings to PE sponsors and executives; and train client teams to maintain deliverables independently.

Own enterprise data governance, metadata, lineage, data quality, master data, GxP readiness, cloud data-layer standards, commercial data controls, partner data exchanges, and AI data governance. Lead federated stewardship, executive scorecards, architecture reviews, access models, vendor data governance, and regulatory readiness across clinical, commercial, and corporate data. Partner with Security, Legal, Privacy, Compliance, and QA while building accountable business ownership and trustworthy, rapidly accessible data.

Build and maintain modern data-centric applications, pipelines, transformations, enrichment processes, provisioning layers, and user interfaces supporting clinical and operational healthcare processes. Analyze clinical data and report trends using cloud, big data, data science, and modern software development practices. Collaborate with Product, Platform, and Architecture teams, mentor Data Engineers, document solutions, manage source control, and research emerging technologies.

Senior individual-contributor analyst leading end-to-end, high-stakes analyses, designing dashboards and reporting, mentoring analysts, applying statistical methods and causal inference, partnering with analytics engineering to shape warehouse models, and translating findings for technical and non-technical stakeholders.

Build and maintain full-stack data engineering solutions supporting BioIntelliSense’s remote patient monitoring and clinical intelligence platform. The role likely involves processing health-monitoring data, enabling analytics, and supporting reporting for clinicians, patients, and employers. Specific responsibilities and qualifications are not provided in the description.

Designs and scales cloud-native data platforms and ingestion pipelines using AWS, Databricks, and Spark. Builds APIs, file-upload mechanisms, ETL/ELT workflows, and Lakehouse architectures; supports SQL Server data loading and legacy C# .NET processes. Partners with analytics, software engineering, architecture, and product teams to ensure data quality and availability for reporting and machine learning. Troubleshoots pipelines and applies governance, security, compliance, documentation, and reliability best practices.

Serves as the technical and client-facing link between Inca Digital’s data engine and high-stakes financial and government clients. Conducts OSINT, web scraping, enhanced due diligence, blockchain and crypto investigations; analyzes large datasets; audits and synthesizes technical findings into intelligence reports; briefs executive stakeholders; and coordinates cross-functional teams to align products with client needs.

Leads data engineering and data science teams, setting strategy and delivering scalable pipelines, data architecture, models, analytics infrastructure, and data governance. Partners with product, analytics, and business stakeholders to prioritize initiatives, assess upstream changes, maintain data quality, and support Snowflake-based warehousing. This hands-on leadership role includes mentoring staff, contributing to technical codebases, and advancing data science and engineering solutions.

Leads the data organization across data engineering, analytics, reporting, and data science. Defines data strategy, architecture, governance, quality, and platform roadmaps; manages and develops technical teams; partners with business and engineering leaders; and guides scalable AWS-based data infrastructure, batch and real-time pipelines, and data products that support strategic growth.