Top Entry Level Data & Analytics Jobs in Columbus, OH

As a Data Operations Analyst, you will maintain and enhance Charge Integrity SaaS by utilizing SQL and data analysis to solve complex revenue cycle problems and ensure accurate charge capture.

Partner with Finance, Accounting, Supply Chain, and Operations to build, automate, and maintain sales, cost, and shipping reports across regions. Develop SQL/BigQuery queries, analyze carrier rates and landed costs, maintain COGS and P&L models, automate recurring reporting, respond to ad-hoc analysis requests, and recommend process improvements.

Analyze policy filings, support ePublishing updates, assist with compliance audits, and collaborate with team members for consistent language implementation.

The role involves data analysis, comparing data across different systems, and making informed business decisions with minimal supervision.

The Data Modeler role involves data profiling, creating source to target mappings, and developing various types of data models including logical, physical, and conceptual, alongside SQL proficiency.

The Data Steward monitors and resolves issues with accounting and insurance policy systems, ensuring data quality and compliance with statutory principles. Responsibilities include reconciliations, reporting, and assisting in month-end closes.

The Advanced Analytics Analyst will provide analytics to support decision-making, focusing on CPG and retail performance insights through data analysis and reporting.

Design, build, and maintain scalable ETL/ELT pipelines and data models to populate the data warehouse. Write reusable SQL and Python to transform data, monitor pipeline reliability and quality, enable AI workflows, collaborate with stakeholders, and drive adoption of modern data stack technologies (DBT, Iceberg, Databricks). Support data governance, observability, and security practices.

Remote entry-level Big Data Engineer role building data acquisition and munging pipelines. Requires strong Python3 (NumPy, Pandas), advanced SQL, scalable algorithm and data-structure implementation on distributed clusters, converting code to functional paradigms, and the ability to learn PySpark or Kafka quickly. Product-development, startup experience and real-world pipeline projects preferred.

Analyze datasets to generate reports and visualizations that inform business decisions. Produce regular reporting, create data visualizations, and work cross-functionally to support data-driven strategies with attention to accuracy.