Top Data & Analytics Jobs in Cleveland, OH

Develop enterprise data warehouse solutions and ETL pipelines using Azure Data Factory, Databricks, Snowflake, and related technologies. Process structured and unstructured healthcare data, including HL7 and FHIR files. Build stored procedures, perform data warehouse modeling, prepare ETL specifications, and use Python, source control, and scripting tools to support data integration and engineering initiatives.

Teaches undergraduate and graduate data analytics courses in an online, technology-enhanced format. Develops syllabi, lesson plans, course materials, assessments, and grading criteria; facilitates learning and provides timely feedback. Integrates responsible AI use, data ethics, and appropriate technology into instruction. Requires a relevant doctorate, applied analytics experience, strong communication skills, and expertise with analytics tools, methodologies, governance, and responsible data practices.

Build scalable Python backend services, data pipelines, and analytics platforms supporting fraud attribute development, machine learning model development, deployment, and monitoring. Design maintainable production systems, implement CI/CD and infrastructure as code, manage AWS and on-premises environments, improve reliability and security, troubleshoot pipelines, and process large datasets for analytics and visualization.

The Manager, R&D Data Modeler designs and governs conceptual, logical, and physical data models for R&D analytics and digital initiatives. Responsibilities include source-to-target mapping, schema optimization, data integration, metadata and naming standards, FAIR and GxP governance, model versioning, architecture workshops, platform implementation consulting, and mentoring junior modelers. The role supports scalable, interoperable data ecosystems for analytics and AI workloads across data warehouses and cloud data lakes.

Build and own AAG’s consolidated data warehouse, including production-grade infrastructure, ELT pipelines, dimensional models, and reporting layers. Integrate data from ERP, CRM, and manufacturing systems into Databricks on Azure, maintain reliable data flows, and support business decision-making across the organization. Collaborate with leadership to translate requirements into code, while managing system development, maintenance, documentation, and continuous improvement.

Supports strategic planning through market, competitor, and trend research; market sizing; benchmarking; SWOT analysis; data synthesis; and reporting. Partners with cross-functional stakeholders to develop insights, identify opportunities and risks, and inform business recommendations. Assists with research projects, presentations, regional and global market assessments, and enterprise planning activities while working under guidance on complex analyses.

Process railroad safety data from receipt through publishing, including logging submissions, scanning and transcribing paper forms, validating reports, and processing inspection and crossing inventory updates. Return incomplete submissions for correction and provide backup Help Desk coverage. The role requires accurate regulatory data processing, Excel proficiency, and basic SQL knowledge, with eligibility to pass a DOT background investigation.

Owns enterprise data architecture across on-premises and cloud systems. Designs data models, integration patterns, governance standards, security controls, and cloud migration strategies. Evaluates data platforms, documents architecture decisions, supports CUI compliance with NIST and CMMC requirements, and partners with technical, security, infrastructure, application, and business teams. Mentors engineers and analysts while communicating technical recommendations to executive and non-technical audiences.

Designs, builds, and operates scalable batch and streaming data pipelines, ETL/ELT workflows, cloud solutions, and secure Python REST APIs. Develops data foundations for machine learning, generative AI, embeddings, and retrieval-based applications. Ensures data quality, security, observability, lineage, and reliability while optimizing performance and cost. Leads architecture and code reviews, establishes engineering standards, mentors engineers, and collaborates with product, analytics, data science, and machine learning teams.

Leads analytics for a designated sub-vertical, serving as the primary analytics partner to Sales and senior clients. Translates ambiguous business questions into actionable insights, manages analytic engagements, supports partner performance, and influences campaign strategy. Uses SQL, AI tools, and compelling storytelling to deliver analysis, QBR narratives, measurement frameworks, and recommendations. Represents analytics in cross-functional and external discussions while helping prioritize team capacity and evolve scalable analytic processes.