Top Senior Data & Analytics Jobs in Cleveland, OH

Owns enterprise-level analysis of client sentiment, health, retention, churn, and journey data. Develops measurement frameworks, health scores, executive dashboards, root-cause analyses, and leading indicators tied to revenue. Synthesizes qualitative and quantitative feedback, identifies systemic experience risks, supports lifecycle improvement initiatives, and presents data-backed recommendations to senior leaders and cross-functional teams.

Design, build, deploy, and operationalize scalable data engineering solutions for customers. Responsibilities include developing pipelines, transforming and cleansing data, analyzing sources, implementing governance, security, and quality practices, testing data movement and transformation code, resolving defects and incidents, and advising customers on technical decisions. The role also supports AI, machine learning, business intelligence, and data product adoption while collaborating across teams and educating end users.

Own end-to-end analytics across marketing, revenue, product, and partnerships. Build reliable data models and semantic layers in a lakehouse, maintain dashboards and monitoring, investigate anomalies, conduct experimentation, and translate complex analyses into recommendations for senior stakeholders. The role requires advanced SQL, Python, data modeling, stakeholder communication, autonomy, and mentoring, with responsibility for improving data quality and building analytical standards in a high-growth startup.

Designs, administers, and optimizes data systems supporting FSA IAM applications. Develops migration plans from legacy AIMS and PAS systems, creates data models, mappings, layouts, dictionaries, and integration processes, and supports analytics and fraud detection. Manages database configuration, performance tuning, monitoring, backups, capacity, secure data handling, encryption, network data flows, token management, and documentation while collaborating with development, security, and operations teams.

Provides data analytics and business intelligence support for government customers. Responsibilities include gathering requirements, analyzing and transforming enterprise data, designing data models, developing dashboards and visualizations, documenting governance processes, improving workflows, and training users. The role requires government acquisition, finance, or financial management experience, preferably within DoD or Air Force systems, and supports financial office operations.

Lead WEX’s semantic data platform and Data-as-a-Service strategy. Define architecture and roadmap, build trusted semantic business objects and governance capabilities, enable AI and agentic applications, and drive enterprise adoption. Lead engineers, architects, and technical leaders while partnering with Product, AI, Analytics, Risk, Finance, and business teams. Translate complex business concepts into scalable platform abstractions and oversee modernization of large-scale data ecosystems.

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.

Drive revenue operations analytics by building reliable data models and dashboards, querying large datasets in Snowflake, ensuring data integrity across the revenue tech stack, and delivering strategic insights to Sales, Marketing, and Customer Success using Looker, Domo, SQL, and scripting.

Transform commercial, market, consumer, and portfolio data into actionable insights. Build and maintain dashboards and KPI reporting, analyze performance and competitive trends, support pricing, assortment, and launch decisions, and deliver executive-ready recommendations while partnering with cross-functional teams to ensure data quality and commercial alignment.