Top Data & Analytics Jobs in Cleveland, OH

Loads, queries, validates, and analyzes data; refreshes databases; prepares client reports; identifies automation opportunities; supports UAT, system implementations, and quality assurance; and collaborates with cross-functional teams. The role requires database management, SQL, Oracle, Unix, Python, Power BI, data modeling, and relational database expertise, with opportunities to use scheduling and master data management tools.

Develop Power BI dashboards, reports, and governed semantic models supporting school operations and student outcomes. Translate stakeholder needs into accessible visualizations, optimize DAX and report performance, implement row-level security, validate data quality, troubleshoot refresh and reporting issues, and support scalable self-service analytics. Collaborate with data engineers, analysts, and business stakeholders throughout requirements gathering, delivery, deployment, documentation, and support while contributing to data governance and reporting lifecycle improvements.

Analyze clinical outcomes, engagement, feature usage, ROI, and business trends for client reporting. Build and maintain complex SQL queries, reporting workflows, interactive dashboards, and self-service analytics. Partner with Customer Success, Sales, Marketing, Finance, Product, and Medical Affairs to deliver actionable insights, executive presentations, and client-facing materials. Improve data quality, automate recurring reporting, and identify opportunities that support client outcomes and business growth.

Build and maintain dbt-based data transformations, analytics models, ELT workflows, testing, and data quality processes. Collaborate with analysts, engineers, and stakeholders to support reporting, self-service exploration, governance, and business decision-making. Troubleshoot data issues, document workflows, evaluate analytics tools, and contribute to scalable data practices using a modern cloud data stack.

Own web analytics for multiple clients, including measurement strategy, data infrastructure, attribution and ROI modeling, tracking integrations, data quality, reporting, and visualization. Present findings to client stakeholders, guide analytics roadmaps, support experimentation and marketing programs, identify risks and opportunities, delegate work, and develop AI-enabled analytics workflows.

Owns Power BI reporting and analytics for Digital, including internal dashboards, campaign pacing, client-facing intelligence products, contact data health, and data delivery monitoring. Builds DAX reporting logic, automated alerts, budget tracking, segmentation, benchmarking, and trend analysis. Partners with IT, Data Engineering, CRM, and audience teams while transitioning an externally developed platform in-house. Serves as the senior reporting subject matter expert for stakeholder and client-facing analytics.

Supports leadership by analyzing business processes, systems, technologies, and operational data to identify improvement opportunities. Maintains and configures business systems, provides second-level technical support, conducts audits, develops reports, validates data, and evaluates workflows. The role acts as a subject matter expert, guides technology adoption, leads initiatives, mentors junior staff, and collaborates across departments to improve efficiency and performance.

Designs, develops, and optimizes enterprise data pipelines and platforms using Snowflake, integrating Oracle Fusion, on-premises databases, and cloud applications. Applies data quality, governance, security, and performance practices while supporting Power BI, AI, and machine learning use cases. Partners with business and technical stakeholders, leads data migrations, translates requirements into sustainable solutions, mentors junior engineers, and guides engineering standards.

Designs and maintains executive dashboards, reports, semantic models, and automated analytics solutions using Power BI. Defines enterprise KPIs, data standards, and business rules while integrating data from ERP, CRM, manufacturing, SQL, and cloud systems. Partners cross-functionally with senior leaders to deliver insights, improve data quality, support master data management, and enable scalable self-service analytics and data-driven decision-making.

Leads end-to-end data architecture, engineering pipelines, semantic-layer development, data quality, monitoring, and platform operations. Manages sprint planning, releases, DevOps metrics, project delivery, and stakeholder communication. Establishes MLOps and machine-learning platform capabilities, mentors data engineers, and ensures reliable, well-documented data solutions that support organizational reporting and analytics needs.