Top Remote Analysis Reporting Jobs in Cincinnati, OH

The Data Governance Analyst administers data governance platforms and processes, including enterprise data catalogs, Databricks Unity Catalog, metadata, lineage, data stewardship, MDM, privacy compliance, and data quality initiatives. The role leads catalog roadmaps, supports Osano, coordinates with data owners and engineering teams, monitors governance adoption and metrics, and develops scalable governance standards and procedures.

Leads the full digital experience research lifecycle, including user interviews, testing, surveys, behavioral analysis, experimentation, and conversion optimization. Defines research and web measurement strategies, analyzes qualitative and quantitative data, builds dashboards and executive presentations, and translates findings into compelling data stories. Partners with marketing, technology, design, product, and development teams to improve global web experiences, while maintaining scalable research documentation and insight repositories.

Leads business and systems analysis for complex mortgage lifecycle initiatives, translating stakeholder needs into business, functional, data, API, integration, and nonfunctional requirements. Develops process and system models, user stories, acceptance criteria, and testing strategies; supports Agile delivery, releases, defect resolution, and post-production validation. Partners with Product, Engineering, QA, and business teams to manage dependencies, risks, and impacts across web, mobile, legacy, and integrated systems. Mentors Business Analysts and improves analysis standards and practices.

Build and lead Surescripts’ commercial analytics function, including governed Salesforce and CRM data models, KPI definitions, dashboards, forecasting, pipeline analytics, customer journey insights, automated reporting, quota modeling, and territory planning. Manage an analyst and partner with Sales, Marketing, Finance, Data, and Business Applications. Present actionable recommendations to senior leaders while improving data quality and enabling self-service analytics.

Lead enterprise database services across Oracle, SQL Server, AWS, and Azure platforms for the Department of Veterans Affairs. Provide technical leadership for database operations, modernization, availability, disaster recovery, security compliance, observability, governance, and performance reporting. Coordinate cross-functional and multi-vendor engineering teams, support cloud transitions and virtualization migrations, maintain audit readiness, and align database services with federal cybersecurity frameworks and VA operational requirements.

Performs business analytics and statistical modeling to identify trends, improve processes, and support decision-making. Develops advanced Excel reports, VBA automations, Power BI dashboards, and data visualizations. Collaborates with business and IT stakeholders, manages shared data in OneDrive and SharePoint, and communicates insights to nontechnical audiences while handling multiple priorities.

Leads end-to-end business intelligence delivery, including requirements discovery, dimensional modeling, SQL development, Power BI dashboards and semantic models, testing, deployment, documentation, adoption, and support. Establishes BI standards, optimizes performance, validates reporting data, partners with stakeholders, communicates analytical insights, and mentors analysts and developers. Requires advanced Power BI and SQL expertise plus practical Microsoft Fabric knowledge.

Analyze credit card sales and business performance using Databricks, SQL, Power BI, and related tools. Optimize lead prioritization and conversion, evaluate customer segments and markets, design A/B tests, and connect sales metrics to revenue, acquisition, and profitability. Present actionable insights and strategic recommendations to cross-functional stakeholders while supporting marketing and business strategy.

Lead development of a unified fleet knowledge model and decision-capture pipeline for autonomous data-center operations. Build data access layers across relational, telemetry, monitoring, and time-series systems; capture labeled operator decisions; negotiate data requirements with source-system owners; and own scaling considerations including vector indexing, schema evolution, retention, and analytics separation. The role requires strong infrastructure-domain modeling, PostgreSQL expertise, and experience handling time-series and event data at scale.

Designs, builds, maintains, and optimizes scalable data pipelines and ETL/ELT workflows using Azure Databricks, SAS, SSIS, SQL, Python, and Spark. Integrates data from internal and external sources, improves performance and reliability, troubleshoots complex processing issues, and supports cloud-based data platform architecture. Collaborates with engineering, analytics, product management, SRE, and other stakeholders to deliver high-quality data solutions.