Top Data & Analytics Jobs in Columbus, OH

Process and analyze datasets, develop and maintain Power BI and Cognos reports and dashboards, troubleshoot data issues, collaborate with stakeholders and technical teams, and document reporting processes. The intern will support business intelligence needs while pursuing a related college degree and working full-time in summer and part-time during the school year.

Designs and maintains BI solutions, writes optimized SQL and stored procedures, and builds AI-assisted reports and dashboards using Power BI, Tableau, and Excel. Translates business questions into actionable insights for Sales and cross-functional teams, develops data models, supports reporting migrations, and ensures data quality, governance, documentation, and consistency across platforms.

Analyze complex construction and design project data, develop datasets, pipelines, reports, dashboards, and predictive or prescriptive models. Partner with business, IT, and data governance teams to address reporting needs, improve processes, establish metrics, manage data access, support governance, and generate actionable insights for capital portfolio decisions.

Designs and maintains scalable cloud data architectures, pipelines, ETL processes, data warehouses, databases, and data models. Ensures data quality, accuracy, security, availability, and consistency across sources. Develops SQL queries for analytics and reporting, and documents pipelines, schemas, architectures, and models. The role requires expertise with Python, Java, Scala, R, SQL, relational and NoSQL databases, cloud platforms, and Snowflake.

Partners with live music venue operations and hospitality leaders to deliver business intelligence, dashboards, reporting, pricing strategies, guest insights, and cost-management analysis. Supports monthly and post-event reviews, data integrity, innovation, and operational excellence initiatives. Builds relationships with clients and stakeholders, experiments with process improvements, and serves as a subject-matter expert for live music programming.

Design and build scalable data engineering and AI agent governance capabilities across major cloud AI platforms. Develop ingestion, processing, ETL, observability, security, lifecycle management, and identity governance features. Evaluate emerging AI agent frameworks and interoperability standards, troubleshoot customer issues, document architecture and processes, and collaborate with engineering, security, compliance, product, and support teams. The role also involves improving distributed data systems, mentoring engineers, and leading technical initiatives.

Own end-to-end data platform architecture across ingestion, lakehouse, warehouse, transformation, modeling, governance, and analytics delivery. Build pipelines, Spark and SQL transformations, data models, and production code. Design Databricks or Microsoft Fabric lakehouses, implement Delta Lake and medallion architecture, establish access controls and governance, and integrate databases, SaaS applications, APIs, files, and legacy systems. Evaluate platform choices based on client workloads, licensing, skills, and cost.

Build and optimize end-to-end data pipelines, production-grade dbt models, BigQuery schemas, Fivetran integrations, and Looker semantic layers. Partner with clinical, operations, finance, and growth teams to translate business questions into analytics projects focused on acquisition, attribution, conversion, and funnel performance. Establish data quality, governance, documentation, testing, and version-control practices while mentoring analysts and supporting secure, compliant data use.

Analyzes complex business processes, data requirements, and information systems supporting the Defense Logistics Agency. Applies DoD Business Enterprise Architecture, data modeling, enterprise architecture, systems integration, and process analysis expertise to improve data quality, interoperability, modernization, and enterprise decision-making. This fully remote role requires Secret clearance and supports AMPS program initiatives.

Own analytics for Customer Success and Operations by translating ambiguous business questions into metrics, reports, dashboards, and PRDs. Partner with senior leaders, CSMs, Analytics Engineers, and Operations teams to improve retention, permit turnaround, and organizational scalability. Build self-service dashboards, develop dbt models, document analytics assets, prioritize high-impact requests, and use LLM tools to accelerate SQL, reporting, and data-model development.