Top Remote Analysis Reporting Jobs in Columbus, OH

Analyzes, validates, and prepares distribution data; develops dashboards, reports, and visualizations; supports warehouse management systems, labor management, configuration, testing, and continuous improvement. Partners with Distribution, IT, process teams, engineers, and vendors to provide business intelligence, troubleshoot systems, communicate data insights, and support operational and strategic decisions.

The Data Analyst position requires U.S. citizenship and that all work be performed within the continental United States, Alaska, or Hawaii. The listed annual pay range is $90,000 to $110,000.

Designs, develops, and maintains Databricks-based ETL pipelines, data lake architectures, datasets, and data quality processes supporting reporting, analytics, and AI/ML workloads. Maintains and migrates legacy SSIS and SQL Server systems, optimizes pipeline performance, and supports complex SSRS reporting. Collaborates with business users, analysts, and IT teams to define data requirements, troubleshoot issues, document solutions, and advance AI-assisted engineering practices.

Lead the design and implementation of scalable data models, transformation pipelines, semantic layers, and analytics engineering solutions. Drive dbt best practices, testing, CI/CD, data governance, quality improvements, performance optimization, and technical standards. Collaborate with analysts, engineers, stakeholders, and clients to translate business requirements into reliable data architectures. Mentor peers, lead technical implementations and delivery workstreams, reduce technical debt, and contribute to shared tooling and frameworks.

Lead design and delivery of scalable, secure cloud data pipelines and products. Translate requirements into architecture, apply advanced data modeling (Data Vault 2.0/dimensional), embed data quality, observability, security, and DataOps/CI-CD practices, optimize performance and cost, mentor engineers, and enable AI/ML-ready datasets within an agile DevSecOps model.

Lead end-to-end analytical initiatives on partner enrollment funnels, ensure data quality, build reporting pipelines with BI/engineering, use AI-assisted tools to accelerate analysis, translate insights into strategic recommendations for leadership, and coach growing analytics team members.

Leads and scales a global data engineering and analytics team while remaining hands-on with architecture, pipelines, data quality, dimensional modeling, dashboards, reporting, and customer-facing deliverables. Owns the analytical data platform supporting clinical, operational, product, financial, and customer data. Partners with cross-functional stakeholders, investigates complex data issues, improves platform reliability and security, and mentors engineers.

The Data Scientist designs and builds data structures for AI applications, manages vector and feature stores, leads data discovery, and collaborates on responsible data use while ensuring high-quality, governed datasets for ML models and applications.

Maintains and updates GIS fiber network data for rural broadband projects using ArcGIS Pro and QGIS. Digitizes and edits vector data, creates network maps and reports, transforms geospatial datasets, applies geoprocessing tools, and performs quality assurance checks. Collaborates with engineers, project managers, and GIS teams to deliver accurate mapping work on schedule.

Lead end-to-end delivery and technical architecture for concurrent clinical and commercial data programs. Guide requirements, data modeling, MDM design, ETL/ELT pipelines, performance planning, testing, UAT, data quality, governance, and production readiness. Champion AI-assisted engineering, define operational guardrails, and coordinate stakeholders, dependencies, priorities, acceptance criteria, and program governance across business and technology teams.