Top Entry Level Data & Analytics Jobs in Columbus, OH

Lead client-facing analytics implementations across Google Analytics 4, Adobe Analytics, and tag management systems. Responsibilities include designing measurement strategies, auditing digital ecosystems, managing tagging and consent platforms, developing data governance and privacy solutions, analyzing performance, aligning KPIs with business goals, presenting insights, supporting proposals, and improving internal analytics standards. Preferred experience includes server-side tagging, data clean rooms, customer data platforms, experimentation, CRM systems, and ETL tooling.

Designs, develops, and maintains data pipelines, workflows, integrations, transformations, and data warehouses. Provides architecture guidance, troubleshoots more than 100 pipelines, supports stakeholders, creates reports, documents processes, participates in code reviews, mentors junior engineers, and translates business requirements into technical solutions while maintaining healthcare data privacy and security compliance.

Own trade performance reporting, dashboards, scorecards, promotional ROI analysis, range review support, category insights, and sales projections for major retail customers. The role turns sales and shopper data into commercial recommendations, supports retailer presentations and new product launches, and collaborates with Sales, Marketing, Supply Chain, Demand Planning, and Finance. It requires strong Excel and presentation skills, commercial curiosity, attention to detail, clear communication, and the ability to manage multiple priorities.

Organize and curate large volumes of raw information: extract key points from transcripts, maintain clean spreadsheets, curate links/resources, tag and categorize content, and follow or propose systems for information structure. Part-time remote role with initial 10 hours/week and potential to grow.

Reviews, develops, validates, and refines dashboards, reports, visualizations, calculations, data sources, KPIs, and analytical workflows across BI platforms. The role documents findings, provides structured feedback, troubleshoots reporting accuracy, and evaluates AI-powered agents and workplace connectors used in analytics processes.

Organise and curate large amounts of raw material: extract key points from transcripts, collate and maintain clean spreadsheets, tag and categorise links and documents, and create findable information structures following or suggesting systems.

Maintain mine-action information management systems, databases, data flows, and quality-control processes. Produce GIS maps, web maps, visualizations, analyses, and prioritization tools using ArcGIS and related platforms. Support mobile data collection, SQL reporting, UNMAS data transfers, staff training, and sector technical working groups. The role supervises data-collection staff and requires English and Arabic proficiency, with rotational deployment in Gaza and regional travel.

Owns analytics datasets and data products for Netflix’s cloud games infrastructure. Builds scalable pipelines, data models, metrics, dashboards, tooling, and self-service assets from massive telemetry data. Partners with infrastructure engineering, data engineering, and data science teams to improve quality of experience, capacity, and utilization insights. Responsibilities include telemetry and logging, visualization, trustworthy documentation, scalable data solutions, and independently prioritizing high-impact investments.

Build and maintain enterprise data pipelines and infrastructure supporting natural-language querying, semantic search, knowledge graphs, and GraphRAG for the SEC. Responsibilities include onboarding data sources, processing XBRL and financial filing data, managing metadata and lineage, validating data quality, monitoring pipeline health, resolving integration issues, and using AWS data services. The role also requires compliance with federal security standards and collaboration with the Data Architect.

Build and operate large-scale data pipelines, web-scraping systems, and data-collection tools for AI datasets. Maintain analytical databases, optimize queries, troubleshoot pipeline and data-quality issues, manage containerized workloads across Kubernetes and Linux infrastructure, and support CI/CD workflows. The role also involves documenting technical processes, researching improvements, and developing scalable APIs in a fully remote environment.