Top Senior Analysis Reporting Jobs in Columbus, OH

Build and own cloud-based data pipelines and governed data products supporting Employee Benefits Sales and Underwriting. Design ELT solutions, integrate complex data, improve data quality, and implement CI/CD and enterprise data engineering practices. Architect hybrid cloud solutions using AWS, Hadoop, Spark, Kafka, Snowflake, and related technologies. Influence architecture and tooling decisions, document technical guidance, mentor teams, evaluate emerging technologies, and contribute to strategic roadmaps.

Develops governed investment data products, pipelines, models, semantic layers, dashboards, and reporting solutions using cloud data platforms. Partners with business and technology teams on requirements, governance, data quality, testing, access controls, and production support. Requires strong SQL, Python, data modeling, Snowflake or Databricks, and BI experience, with preferred financial services knowledge. The role is hybrid in Columbus, Ohio, and does not offer employer-sponsored work authorization.

Analyzes personal lines insurance and digital product performance using SQL, BI tools, statistical methods, and financial modeling. Partners with product, experience, actuarial, finance, and operations teams to identify growth opportunities, optimize digital customer experiences, assess risks, support business cases, and influence leadership decisions. Applies AI and automation to improve analytical efficiency, communicates insights through presentations and reports, and mentors colleagues.

Designs and builds scalable data platforms and pipelines for scientific, clinical, manufacturing, and process-engineering data. Responsibilities include developing batch and streaming ETL/ELT systems, integrating Databricks, Snowflake, cloud platforms, MES, SCADA, and laboratory systems, and enforcing governance and GxP compliance. The role provides hands-on technical leadership, establishes data engineering standards, and collaborates with scientists, process engineers, and platform teams. It requires three days onsite weekly in Indianapolis and unrestricted U.S. work authorization.

The Senior Data Analyst builds and maintains datasets, automated reporting, dashboards, and performance metrics for commercial, operations, and client-facing teams. Responsibilities include healthcare reporting, ad hoc analysis, third-party data integration, SLA and KPI tracking, data quality, governance, lineage documentation, and collaboration with BI and Product Engineering teams. The role translates complex findings into actionable business insights while ensuring accurate, secure, and reliable data for program management and client success.

Designs and maintains enterprise data architecture, models, databases, integrations, cloud platforms, governance frameworks, and AI-ready data solutions. Partners with engineers and business stakeholders to translate requirements into scalable technical designs. Establishes standards for security, reliability, performance, data quality, lineage, disaster recovery, and compliance. Supports reporting, business intelligence, analytics, machine learning, and enterprise data modernization initiatives using Microsoft Fabric, Azure, SQL Server, Azure SQL, Data Factory, warehouses, lakes, and lakehouses.

Ensures healthcare data is accurate, consistent, secure, and compliant. Responsibilities include requirements gathering, SQL-based data preparation, audits, data quality analysis, dashboards, KPI development, discrepancy resolution, statistical modeling, and testing. The role also develops and deploys machine learning and LLM solutions, RAG systems, AI assistants, chatbots, and automation for data quality initiatives, while supporting deployment, documentation, and training.

Leads Vertiv’s global product and item master data strategy, governance framework, standards, lifecycle processes, and operating model. Owns data quality, BOM governance, item classification, and lifecycle management across engineering, manufacturing, supply chain, service, and commercial functions. Partners with IT, PLM, ERP, MDM, and analytics teams on requirements, roadmaps, transformations, and system enhancements. Drives cross-functional alignment, organizational change, stewardship, training, and adoption of globally standardized product data practices.

Design and own scalable data warehouse components, ingestion pipelines, dbt models, marts, and reusable data assets using Snowflake and related technologies. Lead complex initiatives, troubleshoot production pipelines, improve data quality and architecture, collaborate with business and BI stakeholders, and mentor engineers. The role also involves using AI-assisted development tools and supporting reporting, analytics, and executive decision-making.

Leads complex data analytics projects from strategy through completion, delivering predictive models, statistical analyses, dashboards, and actionable insights. Owns data integration, transformation, visualization, experimentation, governance, and ELT quality across Snowflake, DBT, Tableau, and Metabase. Partners with cross-functional stakeholders, mentors analysts, promotes self-service reporting, and communicates findings to leadership. Requires 5–8 years of analytics or business intelligence experience.