Top Senior Analysis Reporting Jobs in Cleveland, OH

Leads managed-services data analytics and business intelligence workstreams for healthcare revenue cycle operations. Oversees planning, budgeting, delivery, dashboards, reporting, data models, and system data flows. Guides teams using Azure Data Factory and cloud data pipelines, ensures analytics quality and security compliance, resolves client issues, mentors staff, and identifies opportunities for automation, advanced analytics, and AI-supported tools.

Leads data strategy for MetLife’s Group Benefits business by connecting business and Data & Analytics teams, establishing shared definitions, resolving ownership gaps, and improving governance and quality. The role leads Data Councils, supports Agile Release Trains, removes data-related blockers, and strengthens data foundations for decision-making, service delivery, analytics, and AI initiatives.

Designs and delivers large-scale, governed data pipelines and infrastructure across the full data lifecycle. Responsibilities include coding in Python and SQL, optimizing Airflow, dbt, AWS, Kafka, and Iceberg/Parquet workflows, implementing data quality and observability, contributing to architecture and tool evaluations, mentoring engineers, collaborating with stakeholders, and participating in on-call support.

Lead complex data analysis across Liftoff’s supply-side business, using optimized SQL on large-scale datasets and BI tools to build dashboards, reporting pipelines, and actionable insights. The role conducts root-cause analysis, evaluates experiments, translates technical developments into business impact, leads cross-functional initiatives, and mentors analysts. It partners with Engineering, Product, Data Science, Finance, Commercial teams, and executive leadership to influence roadmap and operational decisions.

Owns Pfizer GH&B’s AI-ready Snowflake data warehouse, data architecture, ontologies, governance, quality, lineage, access controls, and production reliability. The role supports AI/ML models, dashboards, and business-critical data applications; establishes testing, release, monitoring, and incident processes; directs contingent technical resources; and aligns business-specific data decisions with enterprise standards. Requires strong SQL, Python, Collibra, data warehousing, unstructured-data architecture, ontology, governance, and stakeholder-influence experience.

Own Eve’s go-to-market data models and semantic layer for governed metrics including pipeline, conversion, CAC, win rate, ARR, and bookings. Establish certification frameworks, modeling standards, documentation, alerting, and analytical application patterns across the organization. Partner with Sales, Marketing, Customer Success, and RevOps stakeholders, resolve conflicting metric definitions, enable AI-grounded data tools, review contributions, and mentor analytics engineers.

Analyze and optimize drug pricing using data-driven models, dashboards, reports, and strategic frameworks. Partner with Sales, Operations, Marketing, Finance, Product, pharmacy partners, and data teams to identify opportunities, define success metrics, improve reporting, and balance pharmacy economics with patient affordability. Serve as a trusted analytical advisor and support backend data development and query optimization.

Leads quantitative analytics initiatives that transform complex data into actionable insights and scalable, governed solutions. Responsibilities include stakeholder partnership, self-service analytics development, customer journey analysis, AI and automation application, executive presentations, production reporting support, regulatory compliance, process improvement, and mentoring junior analysts.

Own analytical projects supporting revenue, profitability, and operational performance for the insurance business. Analyze funnels, campaigns, conversions, costs, and trends; build SQL queries and Looker dashboards; automate reporting with Python; define KPIs; validate data; and present actionable recommendations to stakeholders and leadership.

Architects, deploys, and operates scalable data platform infrastructure supporting analytics. Responsibilities include administering Airflow and Superset, managing Terraform infrastructure, building CI/CD pipelines, implementing security and compliance controls, developing dbt data models, cataloging assets in OpenMetadata, automating with Python, and mentoring engineers. The role requires extensive infrastructure and data engineering experience, cloud expertise, container orchestration, and eligibility for CJIS clearance.