Top Analysis Reporting Jobs in Cleveland, OH

Lead the Data Platform Engineering team owning ETL/reverse-ETL pipelines, replication, and production datastores. Define architecture, roadmap, standards (IaC, observability, schema contracts), mentor engineers, drive incident response and durable fixes, and partner on cross-team technical decisions and operational reliability for data correctness, completeness, and timeliness.

Lead analytics engineering for Revenue, Marketing, and Finance by building scalable data solutions, data models, and dashboards; provide training and consultation, support ad hoc data needs, and translate technical findings into executive-level insights to improve operational performance.

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.

Lead architecture and buildout of a new graph-backed enterprise data platform: design ingestion, graph and relational storage, entity resolution pipelines, temporal models, ETL/ELT pipelines, governance, APIs, and production connectors. Ship scalable graph data models, traversal queries, and platform roadmap while enabling observability, security, and containerized deployments.

Manage performance, reliability, and accountability for high-volume messaging programs. Build dashboards and alerting, run ad hoc analyses, coordinate incident response and vendor testing, conduct post-incident reviews, and maintain documentation and compliance tracking to inform program decisions and improvements.

Gather and document business and functional requirements, analyze processes, recommend improvements, produce BRDs/FRDs/user stories and process maps, support solution design, UAT, testing and deployment, produce reports/dashboards, monitor project progress, and support change management and stakeholder communication.

Lead end-to-end lifecycle of curated, governed data products for enterprise domains: prioritize roadmaps, enforce AI-ready standards, drive adoption, define canonical metrics, manage metadata and SLAs, and partner with engineering, governance, and FinOps to maximize business value and cost efficiency.

Participate in a multi-week training then rotate across analytics teams (quantitative modeling, model risk, market risk, fraud, commercial analytics, client/employee experience, credit portfolio). Perform data analysis, develop predictive models, produce reports and visualizations, communicate insights to senior stakeholders, conduct market research, and support financial and regulatory reporting.

10-week summer internship working on data analytics, reporting, business analysis, process and continuous improvement, and project management projects. Includes mentoring, training, and exposure to analytics tools and enterprise technology teams.

Build and maintain financial and operational models and dashboards linking GTM activity to pipeline and revenue. Perform scenario and variance analyses, produce executive-ready narratives, support cross-functional data integration, and drive improvements to reporting, forecasting, and analytical processes.

Lead enterprise data discovery, inventory, classification and governance initiatives. Evaluate and run POCs for tools (OneTrust, BigID, Varonis, Cyera, Delphix, RecordPoint, Collibra, Microsoft Purview). Conduct stakeholder workshops, assess classification accuracy, security, scalability, integrations, and metadata flow. Produce recommendations, feasibility assessments, roadmaps, and support Collibra integration.