Top Analytics Jobs in Cleveland, OH

Own end-to-end product and customer analytics across financial product experiences. Define meaningful metrics, analyze complex datasets with SQL, connect customer behavior to business outcomes, and translate qualitative feedback into product insights. Partner with product, engineering, research, data science, and CX teams to influence roadmaps and senior leadership decisions. Use AI tools such as Cursor and Claude to accelerate analysis and automate workflows.

The Senior Analyst will lead digital measurement analytics for emerging payments platforms, including data collection, validation, reporting, and feature performance measurement. Responsibilities include partnering with marketing, technology, digital, and analytics stakeholders; delivering accurate, compliant projects; communicating insights; supporting strategic priorities; and developing analytics roadmaps. The role requires hands-on problem solving, visualization, web analytics, and collaboration across Agile teams.

Leads data and analytics engineering for Zero Trust maturity assessment and implementation measurement. Designs common data models, integrates and validates enterprise data, develops maturity and risk metrics, supports prioritization and gap analysis, and establishes data quality, lineage, traceability, and documentation practices. Partners with dashboard and automation specialists to streamline reporting and data refresh workflows.

Build and maintain data infrastructure, integrate veterinary partner systems, develop dbt models and pipelines, provide analytics modeling, testing, reporting, and deliver actionable insights to customers and internal teams.

Design and build scalable data foundations, pipelines, semantic models, and AI-grounded tooling. Lead platform-level AE tooling, reusable dbt patterns, observability, cost strategies, and agentic AI workflows. Partner with stakeholders, guide team technical development, and drive cross-functional data initiatives from ambiguous problems to production.

The Data and Analytics Consultant will design, develop, and implement data reporting, visualizations, and analytics solutions for clients while assisting them in data understanding and value extraction.

Lead design and delivery of Snowflake-centric cloud data platforms. Engage with clients to gather requirements, architect scalable secure solutions, provide technical leadership, develop roadmaps, advise executives, and guide implementation best practices across the analytics stack.

Design and implement end-to-end data solutions on Microsoft Fabric and Azure for insurance datasets. Build ingestion pipelines (batch, streaming, API), Lakehouse architectures, and data models. Enforce governance, security, compliance, and cost/performance optimizations while guiding engineers and stakeholders on architectural best practices.

Design and implement end-to-end Microsoft Fabric data solutions (ingestion, Lakehouse, warehouse, real-time). Create architectures, reusable frameworks, and governance patterns for insurance datasets. Lead ingestion pipelines, optimize performance/cost, integrate with Azure services and security, support regulatory compliance, and provide technical direction to engineering and analytics teams.

As a Senior Analyst, you will develop data-driven solutions in collaboration with operations teams and deliver insights through reports and dashboards to improve patient outcomes.

Lead architecture and execution of Faire's data platform and analytics capabilities. Build and operate scalable, secure ETL/ELT, streaming, storage, compute, orchestration, and data warehousing at petabyte scale. Drive performance, cost, monitoring, governance, and self-serve analytics; influence cross-functional teams and mentor engineers.

Lead a small analytics team (staff data scientist + two analysts) to deliver curriculum, product, and program insights. Split time between people management (60-70%) and hands-on analysis (30-40%), advance experimentation and measurement, build AI/LLM-driven agentic workflows, manage sprints and cross-functional stakeholder relationships, and drive analytics that inform curriculum, product, and intervention strategies.

Design and maintain a dbt-based business data layer for GTM metrics, centralize and reconcile multi-source data, implement automated data quality and reconciliation checks, align and document metrics with stakeholders, mentor analytics team, and lead root-cause investigations into complex data anomalies.

Own Backblaze’s analytics transformation and semantic layers using dbt and Snowflake. Build governed data models, certified metrics, lineage, testing, documentation, and auditable financial-reporting data products. Establish engineering standards and scalable delivery practices while partnering with Data Engineering, Finance, Revenue Operations, Marketing, and Business Intelligence. Translate ambiguous reporting needs into trusted entities, metrics, and source-of-truth models, with emphasis on data quality, stakeholder adoption, and AI-ready foundations.

Lead the organization’s analytics strategy, manage a team of analysts, conduct advanced data analysis, and deliver actionable insights to stakeholders. Oversee analytics tools, scalable data systems, and data governance practices while collaborating with marketing, sales, operations, and product teams. The role requires expertise in BI platforms, programming languages, big data technologies, cloud platforms, web analytics, and experimentation tools.

Own the strategy, governance, architecture, modeling, and reporting foundation for People Experience data. Build governed metrics, semantic and consolidated data layers, dashboards, data catalogs, quality monitoring, and operating processes from the ground up. Manage intake, prioritization, access, privacy, enablement, and self-service adoption while partnering with stakeholders on analytics and future AI capabilities. The role combines strategic program leadership with hands-on SQL, data modeling, reporting, and team mentoring.

Owns the end-to-end architecture, development, infrastructure, data pipelines, and Power BI reporting platform supporting data governance, informatics, analytics, auditing, and data quality. Leads and mentors a data engineering team, defines schemas and engineering standards, ensures security and HIPAA compliance, oversees testing and Agile delivery, manages stakeholder requirements, and remains hands-on with backend technologies, data models, Power BI, and DAX.

Manage underwriting analytics, collaborate with cross-functional teams, drive operational improvements, and enhance training for underwriters.

Develop and deliver healthcare analytics solutions using Ursa Studio, reusable data models, data marts, and measures. Partner with clients and cross-functional teams to scope engagements, provide consulting and training, maintain documentation and security standards, and contribute scalable analytics components to Ursa’s SaaS and AI-assisted platforms. The role requires strong healthcare data expertise, SQL proficiency, client-facing communication, and knowledge of healthcare regulations and standards.

Designs and implements big-data data management solutions (Cloudera/Hortonworks/Databricks). Builds and automates reporting and analytics using SQL and Databricks, optimizes queries, manages ETL, integrates multiple data sources, enforces data governance, and supports payment integrity reporting requirements.

Lead design of end-to-end analytics and data solutions, produce architecture diagrams and technical designs, guide delivery teams, run client discovery and requirements sessions, support pre-sales and proposals, build reusable frameworks, and manage and mentor a delivery team to ensure quality and alignment to architecture.

Design and implement ad measurement metrics, perform deep-dive analyses, build reporting and automated pipelines, create visualizations, and provide actionable insights to improve advertiser measurement and platform health.

Partner with Content Finance stakeholders to build and own end-to-end data products and semantic models. Define core metrics, maintain documentation and tests, perform root-cause analysis, improve pipelines, and drive cross-functional alignment. Mentor teammates, champion data-as-product practices, and leverage GenAI tools to accelerate development.

Lead pricing strategy and analytics: develop pricing, packaging and monetization recommendations; build forward-looking revenue/volume models; maintain pricing algorithms and reporting; collaborate with Sales, Finance, Marketing and Data teams to implement pricing actions and standardize quantitative outputs.

Analyze game performance across dimensions (game type, venue, state, device, day), publish quarterly gameplay reports, identify player behavior trends, collaborate with account teams, visualize data with Tableau/Power BI/SAP, and recommend data-driven improvements to boost engagement and revenue.