Top Senior Analysis Reporting Jobs in Columbus, OH

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 and build a product analytics function: define KPI framework, instrumentation, and self-serve analytics using Pendo and BI tools. Partner cross-functionally to measure product performance, surface insights, influence roadmap and embed AI-powered analytics into product lifecycle.

Lead and deliver large-scale customer analytics engagements for Communications, Media & Technology clients. Define strategies, develop thought leadership, drive CRM modeling, reporting and predictive analytics, and grow the client practice.

Lead client-facing marketing analytics projects using SAS and statistical methods. Perform marketing mix modeling, multi-channel attribution, digital analytics, pricing/promotion analysis, demand forecasting, and mentor a team while traveling extensively to client sites.

Implement and configure Teradata solutions and modules across the full systems development life cycle. Collaborate with users to design complex application systems, run workshops and meetings, and adapt software packages to business needs. Provide problem-solving, negotiation, and team-building skills in a fast-paced environment.

Serve as a techno-business SME for reporting and BI tools, using Dataiku, SQL, Tableau, MicroStrategy and Excel to improve analytics. Train teams, drive self-service adoption, lead projects to expand BI ecosystem impact, develop advanced solutions, solve complex problems and mentor junior analysts.

Drive technology risk reporting and analytics for ERM: analyze risk datasets, build Power BI dashboards, integrate IT/IS/third-party data, assess controls using industry frameworks (COBIT, NIST, ITIL, DCAM, DMBOK), support RCSA, and advise business units on risk mitigation and control improvement.

Lead a team in delivering data-driven insights for underwriting and risk selection, managing projects and fostering relationships across business units.

Lead global customer master data strategy, governance, and operations. Build and manage a global team to centralize and harmonize customer lifecycle processes, improve data quality, drive large-scale migrations and platform enhancements, and collaborate with stakeholders to implement roadmaps across data, process, applications, and organizational change.

Design, build, and maintain scalable ETL pipelines and data integration solutions using SQL Server, SSIS, and Azure Data Factory. Lead logical and physical data modeling, create data marts and operational stores, ensure data quality and governance, optimize ETL performance, and collaborate with stakeholders to translate business needs into enterprise data solutions.

Lead onboarding, mapping, and validation for a Customer Data Hub: write user stories and acceptance criteria, define mastering/transformation logic, perform data lineage and reconciliation, validate integrations and outcomes, support production incidents, create runbooks and documentation, and partner with product, engineering, QA, and governance teams to enable reliable customer data for applications and analytics.