Top Remote Data & Analytics Jobs in Columbus, OH

Maintains Looker and LookML dashboards, explores, and reporting infrastructure; supports ad hoc analysis, forecasting, sales pacing, data quality, UAT, vendor management, board reporting, and planning materials during a temporary maternity-leave backfill.

Owns automated dashboards, SQL-based analysis, data pipeline monitoring, exploratory analysis, and executive recommendations. The role tracks marketplace KPIs such as customer lifetime value, acquisition costs, churn, and provider utilization while partnering with engineering and product teams on data requirements. It is fully remote within the United States and requires advanced SQL, dashboard development, and strong analytical communication.

Leads data engineering, business intelligence, and analytics teams; oversees data pipelines, integration infrastructure, database architecture, CI/CD practices, and enterprise data platform strategy. Partners with business and technology stakeholders to define requirements, improve data capabilities, maintain Ubuntu-based services, and deliver reporting and KPIs to leadership. Responsible for team hiring, development, mentoring, operational health, and technical execution across analytics and data integration platforms.

Forecasts contact volume, capacity, and staffing for a virtual healthcare clinic. Monitors real-time queues, adherence, service levels, and intraday risks; combines multiple data sources to create staffing recommendations and reporting. Uses AI and LLM tools to test and improve forecasts, while accounting for clinician licensing constraints. Requires contact center WFM experience, strong Excel skills, analytical communication, and comfort working remotely with required equipment and connectivity.

Build and scale business intelligence solutions that automate processes, integrate and transform data, and deliver actionable visualizations. Partner with business stakeholders to define requirements, develop Databricks workflows and pipelines using SQL and PySpark, collaborate with technology and data science teams, lead project deliverables, and mentor junior team members.

Manage the health, performance, reliability, and cost of customer Snowflake and Databricks environments. Responsibilities include customer onboarding, account and warehouse setup, permissions, data ingestion, query optimization, cost reporting, incident response, escalation support, and automation using Python and Terraform. The role also advises customers and internal teams on data platform best practices and participates in on-call rotations.

Provides analytical and lifecycle support for U.S. Navy electromagnetic warfare, decoy, and SEWIP systems. Applies operations research, data science, logistics analysis, reliability and maintainability engineering, mathematical modeling, simulation, optimization, and what-if analysis to improve system readiness, operational availability, resource allocation, and lifecycle performance. Develops performance metrics, evaluates alternatives, analyzes complex datasets, and delivers recommendations and decision-support products to technical and program leadership.

Owns enterprise data governance activities, including metadata management, data cataloging, data quality rules, lineage, profiling, report certification, PII handling, and governance workflow automation. Partners with data stewards, IT teams, business stakeholders, and senior leaders to improve data integrity, regulatory compliance, reporting quality, and governance processes. The role also supports training, stakeholder workshops, process improvement, and mentoring of less experienced professionals.

The job description is incomplete. Based on the available text, this role appears to support pathology data activities within a clinical laboratory environment.

Analyzes operational data, builds and maintains reports and Power BI dashboards, develops data processes and pipelines, validates data quality, monitors KPIs, and presents insights to leadership. Partners with Operations, Quality Assurance, Dispatch, engineering, data science, and product teams to answer business questions, improve reporting, support analytical projects, and inform operational decision-making.