Top Data & Analytics Jobs in Cleveland, OH

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.

The Data Entry Specialist will input data accurately, requiring strong attention to detail, speed typing skills, and proficiency in MS Excel and Salesforce.

Lead design and implementation of a global product master data management solution using Oracle Product Hub. Configure PIM, integrate Product Hub with Oracle EBS and non-EBS systems via middleware, and drive execution with client IT teams.

Provides production support and administration for mission-critical SQL Server, PostgreSQL, AWS, and Databricks environments. Monitors performance, resolves incidents, performs root-cause analysis, develops database objects and ETL pipelines, and designs scalable lakehouse data models. Supports data migration, governance, validation, reporting, monitoring, and analytics while collaborating with architecture, development, product, and agency stakeholders in an Agile environment.

Lead FranklinCovey’s research and measurement agenda, data product strategy, applied behavioral research, and thought leadership. Manage researchers, design rigorous studies, conduct statistical analyses, evaluate data fitness, develop benchmarks, and measure behavior change and business outcomes. Partner with Product, Technology, legal, sales, and marketing teams to translate research, AI, and analytical methods into data-driven products, personalized recommendations, and client insights. Ensure responsible data use, privacy, methodological rigor, and clear executive communication.

Leads complex data analysis and business intelligence initiatives supporting revenue forecasting, profitability, operational planning, and business performance. Builds analytical models, queries, dashboards, reports, and data workflows using SQL and Python. Resolves data-quality issues, improves processes, communicates actionable insights, and coordinates with business and technical teams. Mentors analysts, reviews analytical work, and provides technical guidance on data visualization and analytical methods.

The Data Engineer II supports customer workload onboarding through requirements gathering, query conversion, schema design, metadata analysis, data loading, workload testing, and performance analysis. The role collaborates with Solutions Architects and engineering teams to prepare pre-pilot workloads, create validation assets and technical documentation, assist with system sizing and timelines, and contribute to GDPR and data rolloff procedures.

Leads Global Fund for Children’s learning, evaluation, and impact function. Builds learning infrastructure, stewards outcomes frameworks and theories of change, guides mixed-methods research, and embeds participatory, trust-based learning practices across programs. Manages the Learning and Evaluation team, data governance, knowledge systems, and organizational reflection processes. Synthesizes evidence and stories for leadership, the Board, donors, and external audiences while protecting the dignity and safety of children, youth, and communities.

Build and maintain governed gold-layer data products, semantic models, standardized metrics, Power BI reports, and AI-enabled experiences. Design and deploy RAG solutions, AI agents, embeddings, and automated workflows using Microsoft Fabric and Azure AI Foundry. Apply security, governance, monitoring, testing, deployment, and documentation standards. Own technical delivery from design through production support, conduct proofs of concept, mentor peers, and enable adoption across plant and business teams.

Lead the design and implementation of a scalable contract data model, including migration strategies, data architecture, pipelines, warehouses, analytics layers, governance, security, and quality monitoring. Partner with Product, Engineering, Data Science, ML, Professional Services, and customer-facing teams. Drive architecture decisions, provide technical mentorship, lead reviews, and manage multi-quarter data initiatives for a SaaS platform.