Top Senior Analysis Reporting Jobs in Columbus, OH

Senior Business Intelligence Analyst who develops and governs Power BI dashboards, analyzes clinic performance metrics, ensures reporting accuracy, and translates operational needs into technical requirements. The role manages BI projects end to end, prioritizes analytics tickets, presents insights to executive stakeholders, establishes reporting standards, contributes to data-model requirements, and mentors junior analysts across clinical and corporate operations.

Leads enterprise business intelligence and analytics solutions using Power BI and Microsoft Fabric. Designs semantic models, certified datasets, dashboards, DAX calculations, data transformations, security controls, and governed self-service analytics. Assesses and modernizes reporting portfolios, develops predictive and forecasting capabilities, gathers requirements, validates data quality, supports documentation and adoption, and mentors analysts. Collaborates with business, engineering, governance, and security stakeholders to establish scalable enterprise analytics standards.

Customer-facing technical leader who architects, builds, and optimizes large-scale data engineering and lakehouse solutions on Databricks. Supports pre-sales and delivery with POCs, performance/load testing, workload sizing, migrations, observability, and adoption through workshops and community engagement.

Own the Finance and Operations data layer, integrating systems into Snowflake and Omni, building reusable data models, dashboards, governed metrics, validation checks, and reconciliation workflows. Partner with Finance, Operations, and Data teams to translate business processes into trusted analytics, improve data quality, automate reporting, and support leadership decision-making.

Analyzes healthcare claims, provider, pharmacy, and enrollment data to identify trends, improve data quality, optimize workflows, reduce costs, and support business decisions. Translates business needs into requirements, develops complex SQL queries, validates data, recommends process improvements, coordinates projects, and serves as a liaison among operations, research and development, IT, and external partners. Also mentors team members and communicates technical findings to nontechnical stakeholders.

Owns and codifies business definitions and calculation methods for legal spend analytics, audits legacy Excel/PowerPoint artifacts, validates analyses (SQL and AI), supports reporting and storytelling for senior law department and C-suite audiences, and helps migrate analyses into modern analytics tooling.

Lead architecture and hands-on engineering to design, scale, and govern a cloud-native lakehouse using Databricks and Microsoft Fabric. Build batch/streaming pipelines, ensure HIPAA-compliant PHI handling, produce analytics-ready datasets, mentor engineers, and drive platform strategy, governance, and reliability.

Develops and manages enterprise business intelligence products, including semantic models, governed definitions, metadata, dashboards, and AI-assisted analytics capabilities. Translates complex business needs into measurable analytic solutions, advises stakeholders, supports adoption and training, and manages product lifecycle, quality, performance, and business impact. Partners with product managers and business leaders to prioritize work, manage risks, communicate value, and guide less experienced team members.

Own and evolve the analytics platform, including data models, pipelines, metric definitions, semantic layers, dashboards, and self-service data products. Partner with cross-functional stakeholders to translate business needs into reliable technical solutions. Lead data initiatives, improve ELT reliability and governance, resolve quality issues, mentor teammates, and shape the Analytics team’s technical roadmap. The role requires strong SQL, dbt, modern data-stack experience, business communication, and independent execution in an ambiguous environment.

Owns retention analytics for a new Loyalty & Retention organization, including churn definitions, survival analysis, forecasting, experimentation, acquisition attribution, satisfaction analysis, payment recovery, and save-desk performance. The role builds reporting and predictive models from scratch, partners with BI and actuarial teams, influences cross-functional decisions, and presents retention findings and forecasts to executives.