Top Data & Analytics Jobs in Cleveland, OH

Conduct individual and institutional prospect research, donor profiling, pipeline qualification, due diligence, and risk assessments. Synthesize financial, philanthropic, and relationship information into briefings, event snapshots, leadership summaries, and board bios. Proactively identify new donor prospects, monitor wealth and philanthropic trends, and support board and geographic expansion initiatives. Train Development staff on research tools, establish service protocols, and manage research requests independently while protecting confidential information.

Own GTM reporting and analytics across Salesforce, warehouse systems, Tableau, and Excel. Build trusted dashboards, define metrics, investigate data quality issues, and lead analysis for pipeline, forecasting, territory design, capacity planning, productivity, and resource allocation. Partner with GTM, CRM, Data, and Systems stakeholders to improve reporting architecture and support leadership decisions. Use AI tools to automate analysis and develop internal analytics workflows.

Build and own the data platform backbone: design ingestion patterns, Snowflake warehouses, governance, and freshness strategy. Implement reliable batch and streaming pipelines, data quality, observability, and onboarding processes. Lead legacy migrations, create data contracts and SLAs, and apply AI-native tooling to automate debugging, documentation, and operational workflows while partnering with Analytics, Engineering, and vendors.

Own the companys end-to-end data graph, ensure data quality and lineage, and deliver Sigma dashboards and client-facing reports. Act as single owner for triage, prioritization, and translation of business questions into actionable insights, partnering closely with data engineering and business leaders to set standards for production-ready reporting.

Manage daily Data team operations, research and analyze datasets, build internal and external reports (including an annual Startup Ecosystem Ranking), and maintain/improve Python scripts and data infrastructure to deliver actionable insights.

Design and build Snowflake transformation layer and migrate legacy SQL to versioned dbt models. Define conformed dimensions/facts using Kimball principles, set modeling and CI/CD standards, implement data quality/lineage, support BI migration and AI/ML readiness, and mentor future hires. Hands-on work in dbt, SQL, and Python with stakeholder collaboration and governance for financial and operational data.

Build and maintain CS reporting, dashboards, and health score models to identify renewal risk and inform strategy. Deliver executive reporting, collaborate cross-functionally to improve data quality, and develop predictive analytics and longitudinal tracking to reduce churn.

Manage and mentor a data engineering team while leading Snowflake-based platform architecture, enterprise data integrations, governance, observability, and pipeline reliability. Partner with analysts, business leaders, product management, and engineering teams to improve trusted self-service data access. Establish engineering standards, modernize the data stack, optimize costs, and deliver an AI-ready data foundation supporting analytics, reporting, and future AI initiatives.

Lead enterprise data strategy, governance, and operating model. Align data initiatives to business value, oversee data lifecycle, security, compliance, and analytics capabilities. Define org structure, KPIs, and delivery frameworks while driving large, multi-platform integration initiatives and process execution.

The role involves acting as a subject matter expert in Data and AI, providing technical expertise during sales processes for Azure-based solutions, and mentoring team members to enhance client experiences.