Top Data & Analytics Jobs in Cleveland, OH

Lead and grow an analytics engineering team to build a trusted semantic metrics layer, scalable dimensional models, and governance. Partner cross-functionally to deliver reliable data products, improve pipelines and observability, set technical standards, and enable self-service analytics, experimentation, and ML while balancing scalability and business impact.

Design and implement data engineering and reporting solutions for MarTech/AdTech clients: build data models in BigQuery/dbt, manage ETL pipelines, create dashboards in Looker/Data Studio, validate integrations, and collaborate with product and engineering teams to scale reporting and analytics.

Perform default reporting and analytics for mortgage servicing portfolios, validate and troubleshoot data and exception reports, conduct root-cause analysis, produce ad-hoc reports, document processes, and collaborate with default management to ensure regulatory-compliant, accurate reporting delivery.

Process, validate and QA large survey datasets; produce datasets, tables, codeframes and documentation; support weighting, testing and statistical analyses; learn and apply Python/R, automation and AI-assisted tools; improve automated processing workflows under senior guidance.

Provide MEAL technical advice and capacity strengthening to country teams and partners across RAPID and EMPOWER projects. Support MEAL system design and implementation, digital data-collection tools (Kobo/CommCare), data management, analysis, visualization, feedback and complaints systems, proposal MEAL components, and documentation. Conduct trainings, capture lessons learned, and represent CRS with donors and partners to improve program quality and accountability.

Lead and develop a team delivering enterprise data engineering, analytics, and governance. Oversee data pipelines, ETL/ELT, cloud platforms, integration services, and stakeholder engagement to enable data-informed decision-making across the university system.

Design, build, deploy, and maintain large-scale analytics solutions and ETL pipelines. Implement real-time streaming and batch processing, optimize SQL and data flows, ensure data quality, contribute to dev-ops and QA, cross-train team members, and participate in community and best-practice activities.

Own and build customer health, usage/adoption, and product configuration data models. Produce ad-hoc and recurring analyses to identify upsell/expansion opportunities, partner with CS, Sales, Product, and Data teams, and present actionable insights to leadership to drive revenue-relevant actions.

Build and support high-performance data solutions, design and operate ETL pipelines and data warehouses, monitor production analytics tools, troubleshoot system issues, collaborate with product teams, and support TechOps for analytics infrastructure.

Design and own data migration strategy and architecture. Map source-to-target data models, build data dictionaries, perform migrations and testing, reconcile results, and collaborate with stakeholders and project teams to ensure successful modernization.