Top Senior Data & Analytics Jobs in Cleveland, OH

Build and own production data infrastructure for a healthcare AI platform. Responsibilities include REST API ingestion, Azure Event Hubs streaming into Databricks, Delta Lake medallion pipelines, entity resolution, semantic metrics, data-quality instrumentation, reconciliation, schema-drift handling, and troubleshooting source-to-warehouse discrepancies. The role requires strong Python and SQL skills, independent pipeline ownership, and experience with Databricks, Spark, PySpark, streaming, and healthcare-related data is a plus.

Leads quantitative and qualitative market research on international development, AI adoption, institutional demand, funding, procurement, competition, and commercial opportunities. Evaluates AI and data service applications, develops market assessments and strategic recommendations, manages research initiatives, prepares executive presentations, and collaborates with leadership, technical, operational, and business development teams to support market entry and growth.

Build and guide data platform capabilities supporting marketing, finance, analytics, and data science. Develop data collection, integration, scoring, experimentation, analytics, and infrastructure solutions; contribute code, lead cross-functional technical initiatives, improve system resiliency through incident response, and establish engineering standards. Partner with business and technical stakeholders to define strategy and long-term roadmaps.

Owns DeVry University's website measurement ecosystem, including GA4, GTM instrumentation, event taxonomies, data quality, tracking governance, and conversion measurement. Analyzes SEO, AI search visibility, website journeys, acquisition, engagement, and conversion performance using SQL and dashboarding tools. Investigates anomalies and friction, supports experimentation, automates monitoring, and delivers prioritized recommendations. Partners with web, marketing, SEO, technology, analytics, and external teams to improve measurement reliability, digital experience, and prospective student conversion.

Build and support production analytics models using SQL, dbt, BigQuery, Looker, and LookML. Develop governed semantic layers, self-service analytics, automated tests, and reliable datasets for business and AI use cases. Partner with stakeholders to translate ambiguous requirements into reusable solutions, investigate data discrepancies, optimize performance, support platform modernization, and maintain data quality, privacy, and documentation.

Leads enterprise advanced analytics and modeling to identify drivers of business performance across brands, markets, customers, accounts, and geographies. Translates findings into prioritized actions, playbooks, launch strategies, and scenario-based recommendations. Oversees rigorous, scalable analytical approaches, partners with senior stakeholders, and develops analytics talent across the organization.

Builds business-critical dashboards, scorecards, reports, and ad hoc analyses using SQL, Python, Excel, Power BI, and Tableau. Analyzes KPIs, identifies trends and root causes, automates recurring reporting, validates data, and translates complex findings into actionable insights for stakeholders and leadership. The role collaborates with data engineers and cross-functional teams to improve reporting workflows, data pipelines, and decision-making.

Own the architecture and standards for a trustworthy BI analytics platform. Design data models, ingestion and transformation patterns, lineage, PII controls, reliability SLAs, observability, schema governance, and cost management. Partner with engineers, analysts, business leaders, Security, Legal, and Compliance; enforce testing, CI/CD, infrastructure as code, and data quality practices. Mentor data professionals and document architectural decisions.

Owns end-to-end customer analytics workstreams, including KPI frameworks, multi-source dashboards, reporting, data governance, quality assurance, and insight delivery for government digital communications programs. Presents recommendations to stakeholders, mentors junior analysts, leads Agile ceremonies, documents analytics practices, resolves data issues, and evaluates AI-assisted analytics tools.

Senior Data Manager acquires, validates, integrates, protects, and manages enterprise data throughout its lifecycle. The role develops ETL solutions, data architectures, models, stored procedures, reporting datasets, and visualizations using Databricks, SQL, and cloud technologies. Responsibilities include translating business needs into technical requirements, leading data projects through deployment, analyzing complex data, improving processes, and supporting business decisions through accessible insights.