Top Data & Analytics Jobs in Columbus, OH

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.

Analyzes complex healthcare data to identify trends, develop statistical and machine learning methodologies, and produce actionable insights. Builds dashboards and reports, supports product and business decisions, promotes data literacy, and collaborates with cross-functional teams. The role also ensures analytics practices comply with healthcare privacy, governance, security, and regulatory requirements, including HIPAA.

Analyze Customer Care performance, trends, KPIs, and data quality; gather reporting requirements; define metrics and business rules; validate data solutions; develop dashboards and visualizations; and translate findings into actionable recommendations. The role partners with business leaders and technical teams to modernize legacy reporting, improve scalability, ensure data accuracy, and enable self-service analytics.

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.

Support digital tools, technology initiatives, project workflows, data management, visualization, and technology-enabled solutions. Collaborate with technical professionals to improve engineering and design team workflows, apply classroom knowledge to real-world challenges, and participate in professional development and networking activities.

Collects and analyzes internal and external data to identify trends, opportunities, and risks. Develops dashboards, reports, and visualizations for leadership; monitors KPIs; partners with advisors to answer business questions; and supports strategic planning through forecasting, modeling, and scenario analysis.

Summer technology intern supporting data analytics solutions, including SQL and Python data extraction, transformation, pipelines, reports, and Tableau dashboards in Snowflake. The role applies AI/ML, predictive analytics, natural language querying, and GenAI-assisted analysis to business decision-making. Interns collaborate in Agile teams, refine development backlogs, learn emerging technologies, and build cross-functional relationships.

Leads Northwest Bank’s enterprise data governance program, including data policies, quality rules, lifecycle management, metadata, master data, stewardship, governance tooling, and remediation. Facilitates Data Working Groups, investigates root causes, manages governance metrics and reporting, demonstrates tools, documents processes, and supports training. Partners across a matrixed organization to ensure data assets meet standards, controls, regulatory requirements, and business needs.