Top Senior Analysis Reporting Jobs in Cleveland, OH

Analyze personal loan product performance, customer behavior, funnel conversion, campaigns, and key performance metrics. Design measurement frameworks, identify tracking gaps, conduct root cause analysis, develop A/B tests, support analytics infrastructure, and create dashboards. Partner with Product, Engineering, Data Science, and Business teams to translate insights into product improvements and increased origination volume.

Analyzes complex business data to identify trends, develop models, dashboards, and actionable insights. Collaborates with leaders and cross-functional teams, supports data governance, validates data integrity, applies statistical and predictive techniques, and communicates findings to technical and non-technical audiences. Provides mentorship to junior analysts and may lead projects. Occasional business travel may be required.

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.

Design, build, and optimize enterprise ETL/ELT pipelines, cloud data lakes, lakehouse solutions, data models, and semantic layers across AWS and Azure. Ensure data quality, security, performance, reliability, and governance while supporting analytics, reporting, and AI initiatives. Collaborate with product, engineering, IT, and business stakeholders to translate requirements into scalable data solutions, monitor pipeline health, troubleshoot issues, and improve data architecture and practices.

Own Step’s analytics data models, transformation pipelines, metric definitions, semantic layer, and data quality practices. Partner with Product, Marketing, Engineering, Risk, Growth, and Finance to establish trustworthy data foundations and enable self-service analysis. Build reusable query, visualization, and code components; apply AI-augmented workflows; and collaborate with data scientists, analysts, and platform engineers. The role requires strong SQL, modeling, pipeline, BI, communication, and independent ownership skills, with occasional travel for team onsites.

Conducts econometric, causal, statistical, and optimization analyses to improve operational efficiency, resource allocation, product performance, and business outcomes. The role defines efficiency measures, develops forecasting and optimization tools, partners with product and engineering teams on data instrumentation and implementation, and communicates findings to executives through clear reports.

Owns lead and hotel account data quality for a sales organization. Responsibilities include CRM audits, deduplication, enrichment, lead qualification, routing, SLA development, escalation resolution, data workflow documentation, vendor evaluation, SQL-based validation, and responsible use of AI for quality assurance and anomaly detection.

Owns a six-month analytics engineering engagement covering scalable Snowflake architecture, marketing and sales ingestion, finance automation with LLM agents, data reconciliation, and governed Tableau reporting. Builds production-ready pipelines, data models, quality monitoring, human-in-the-loop controls, and row- and column-level security. Delivers documentation and knowledge transfer while coordinating independently with finance and publishing stakeholders.

Administers and optimizes enterprise Oracle databases supporting global consular applications. Responsibilities include database operations, backup and recovery, replication, disaster recovery, performance tuning, security remediation, SQL and PL/SQL development, upgrades, migrations, monitoring, governance, documentation, and operational support for Oracle RAC, Data Guard, GoldenGate, and Oracle Linux environments.