Top Data & Analytics Jobs in Cleveland, OH

Manages a business analytics team that delivers insights, KPI reporting, trend analysis, data visualizations, governance, and actionable recommendations. Guides statistical analysis, data modeling, querying, experimentation, and self-service analytics while aligning practices with enterprise standards. Partners with leaders to identify opportunities and risks, improve data quality, drive analytics adoption, and support strategic and operational decisions. Oversees team performance, department projects, communications, and best-practice development.

Leads global people analytics and workforce intelligence strategy, building AI-driven tools, predictive models, dashboards, and decision-support applications. Partners with IT, data, and security teams on governance, privacy, and ethical AI. Advises executives, democratizes workforce insights, measures people-program ROI, and anticipates talent trends through benchmarking and workforce modeling.

Optimize and administer SQL Server databases supporting multi-terabyte healthcare claims data. Responsibilities include tuning T-SQL, execution plans, indexing, partitioning, statistics, tempdb, memory, backups, high availability, and database monitoring. The role develops stored procedures and data structures, identifies claims overpayments, automates data mining processes, investigates root causes, and mentors analysts. Collaboration with infrastructure and business teams is required, along with ownership of small projects and performance improvements.

Leads strategy, planning, and execution of customer EMR integrations for PhareOS. Oversees end-to-end data delivery, integration quality, process standardization, tooling, vendors, and platform enhancements. Builds and scales the data integration team, manages resources and senior client stakeholders, and drives innovation across integration methods and operating models. Requires extensive healthcare data integration leadership, HL7/FHIR and interface engine expertise, SQL proficiency, and strong program management skills.

Build and govern clinical analytics datasets, SQL transformations, data marts, dashboards, and reporting solutions for clinical quality, patient safety, outcomes, regulatory, and research initiatives. Partner with clinicians, executives, researchers, and enterprise data teams to define metrics, ensure data integrity, implement testing and governance frameworks, and deliver trusted executive, board, regulatory, and clinician-facing insights using modern cloud data platforms.

Design and modify data solutions using Databricks and Palantir Foundry; build data models and reports from ERP and legacy-system datasets; define and execute tests; and translate stakeholder reporting needs into technical specifications. The role requires SQL, Python, PySpark, database architecture, cloud architecture, software engineering practices, independent execution, documentation, and collaboration. It supports an Army client in a hybrid Arlington, Virginia environment and requires an active Secret clearance.

Lead advanced Amazon and commerce analytics using Amazon Marketing Cloud, advertising, and retail data. Build queries, dashboards, reports, tests, forecasts, and actionable client-ready recommendations. Partner with client, media, operations, data science, and reporting teams to support investment, optimization, and retail decisions. Ensure analytical quality, documentation, automation, and measurement rigor while identifying growth opportunities and communicating technical insights to clients.

The Senior Data Analyst will support Growth and Product teams through paid-channel analysis, user journey optimization, activation and retention insights, and churn reduction. Responsibilities include developing experiments, analyzing ad network performance, improving tracking and instrumentation, ensuring data quality, and enabling self-service analytics. The role requires translating complex data into actionable recommendations and communicating effectively across technical and non-technical teams in a fast-paced SaaS environment.

Leads the enterprise business intelligence and analytics strategy, manages BI and data analysts, and oversees analytics roadmaps, projects, platforms, dashboards, and vendor relationships. Translates complex data into actionable financial and business insights, supports SAP and Power BI platform upgrades, manages delivery timelines and resources, and coaches team members. The role also drives stakeholder engagement, continuous improvement, talent development, and data-driven decision-making across the organization.

The Business Intelligence Engineer manages enterprise data sources, supports data quality and governance, and translates transactional data into KPIs for business teams. Responsibilities include guiding analyst teams, handling data inquiries, supporting advanced analytics, monitoring data performance, defining data requirements with stakeholders, and presenting findings to technical and non-technical audiences. The role requires SQL, Tableau, relational database, and data modeling or analytics expertise.