Top Data & Analytics Jobs in Cleveland, OH

The AVP, Data Engineer will design and build data ingestion, transformation, and replication pipelines using SQL, Python, dbt, and Dagster. Responsibilities include translating requirements into technical designs, developing data products, debugging production issues, supporting testing, and improving data engineering practices. The role also involves data modeling, mentoring junior engineers, conducting code reviews, and providing technical leadership while remaining hands-on. Experience with modern data platforms, workflow orchestration, cloud ecosystems, and insurance or financial services is preferred.

Serves as the liaison between business stakeholders and ServiceNow developers, gathering requirements and mapping business processes to workflows. The role supports dashboards, KPIs, performance analytics, data validation, cleansing, transformation, testing, UAT, documentation, data governance, compliance, training, and process optimization. It develops user stories, acceptance criteria, and test scripts while helping federal agencies improve ServiceNow reporting, workflow automation, and operational performance.

Build and operate large-scale audio data pipelines for AI model training. Responsibilities include discovering data sources, improving data-processing systems for quality, throughput, and cost, collaborating with AI scientists, and owning engineering projects through continuous improvement.

Designs and maintains secure, reliable data platforms, including relational data models, migrations, pipelines, monitoring, data quality processes, and self-service reporting access. The role protects PHI and PII through access controls, encryption, audit logging, and governance in a HIPAA environment. It also involves backend API development, code reviews, security reviews, stakeholder collaboration, and mentoring teams on data practices.

Manages HR data, analytics, reporting, dashboards, pipelines, integrations, and automation. Supports compensation, performance management, workforce planning, HRIS maintenance, and employee listening initiatives. Builds data models and AI integrations, audits data integrity, develops actionable insights, and presents findings to HR and executive leadership. Requires strong compensation expertise, advanced Excel, HRIS and BI experience, scripting, data modeling, and handling confidential information.

Supports dataset collection, cleaning, analysis, visualization, reporting, A/B testing, and performance tracking for education products. The intern will identify trends in student, educator, and product usage data, build dashboards, document analytical frameworks, and communicate insights to technical and non-technical teams. This is a paid, remote 10-week internship with a two-day in-person experience at Amplify headquarters in Brooklyn.

Leads healthcare quality analytics using hospital performance, national rankings, Medicare claims, and CMS data. Replicates quality methodologies, identifies improvement opportunities, builds dashboards and benchmarking tools, and establishes analytic validation standards. Presents insights to executives and customers, supports pre-sales and engagements, partners with data scientists and consultants, and mentors analysts.

Designs, develops, tests, and executes SQL-based data migrations and integrations for higher education Advancement systems. Builds data pipelines, staging tables, transformation logic, stored procedures, validation processes, and database-driven integrations connecting legacy platforms, institutional databases, and Salesforce. Configures Salesforce, troubleshoots data and performance issues, supports migration testing and deployments, and collaborates with architects, consultants, and client stakeholders. Periodic travel and client relationship development are required.

The Analytics Manager analyzes complex datasets, builds models, conducts scenario analyses, and provides strategic recommendations to guide decision-making for leadership.

Analyze marketing performance and ROI across markets, identify expansion opportunities, evaluate market saturation and competition, and support investment decisions. The role requires advanced SQL, funnel analysis, dashboard development, multi-source data integration, statistical reasoning, and clear communication of recommendations to marketing and leadership. The analyst will also use AI tools such as Claude and partner with data engineering to improve data quality and decision support.