Top Data & Analytics Jobs in Columbus, OH

Lead architecture, development, and optimization of a cloud-native data platform. Design high-volume batch and streaming pipelines, optimize data processing across AWS, Snowflake, Redshift, and Athena, and implement Iceberg-based data management. Establish security, privacy, observability, and DataOps practices while mentoring engineers, guiding technical direction, collaborating with data science teams, and delivering scalable petabyte-level data infrastructure.

Develops scalable data and software systems using Python and Apache Spark. Designs APIs, data models, ETL workflows, orchestration, and data interactions while optimizing performance, scalability, integrity, and security. Builds user interfaces, contributes to automated testing, applies Agile practices, and supports CI/CD delivery. The role requires strong software engineering, distributed computing, analytical, and communication skills, with AWS, R, Databricks, and SAS experience preferred.

Leads advanced analytics for Tribal healthcare initiatives, including data resource inventories, quality assessment, linkage analysis, predictive and prescriptive modeling, dashboards, and management reporting. Develops data standards, quality frameworks, automation, and infrastructure strategies while ensuring federal compliance. Coordinates cross-functional analytics projects, supports healthcare quality measures, mentors junior staff, and promotes data-driven decision-making using Python, R, SQL, statistical methods, and machine learning.

Provides senior database administration and engineering for Navy MFOM application and infrastructure environments. Responsibilities include database design, implementation, testing, maintenance, upgrades, security, performance, backup and recovery, modernization, cloud integration, incident resolution, and technical documentation. Coordinates database changes and risks across software, systems, infrastructure, cybersecurity, and government stakeholders while providing technical leadership and continuity for mission-critical database operations.

Develop and optimize SQL Server and SSIS billing pipelines, automate data movement and validation with Python, and use R and Python for analytics, anomaly detection, and billing decision models. Build data-quality frameworks, support internal reporting tools, integrate ERP APIs, and collaborate with finance and operations stakeholders. The role requires maintainable, tested, auditable solutions and ownership of features across databases, pipelines, analytics, and internal applications.

Designs and builds enterprise-scale Azure lakehouse platforms for claims data using Databricks, Spark, Delta Lake, PySpark, and SQL. Responsibilities include developing Medallion Architecture, ETL/ELT pipelines, data models, governance, access controls, lineage, performance optimization, CI/CD, and production support. The role translates business and data requirements into technical designs while partnering with engineers, analysts, and stakeholders.

Own marketing channel performance tracking, reporting, experimentation, dashboards, forecasting, and LTV analysis. Develop measurement frameworks, identify data issues, and translate complex findings into actionable recommendations for Marketing, Growth, Product, and Finance stakeholders. The role requires strong SQL, BI dashboarding, marketing measurement, experimentation knowledge, and effective analytical communication, with AI tools used to accelerate reporting and analysis.

Build and maintain a production data platform integrating RMS, Azure SQL, HubSpot, and vendor APIs. Develop pipelines, data models, quality gates, APIs, system-of-record write-backs, performance improvements, and explainable lineage. Build production AI-agent workflows with evaluation, guardrails, and monitoring. Own features end to end, contribute to applications, support incident response, and collaborate with product managers and traders.

Lead production of federal species range maps for marine and anadromous taxa. Aggregate, normalize, transform, and validate spatial data; analyze habitat intersects; coordinate iterative reviews with FWS and NOAA SMEs; prepare QA documentation; and secure government sign-off for map deliverables.

Design, build, deploy, and maintain AWS-based data and AI/ML infrastructure for enterprise agentic AI platforms. Develop data lake pipelines, observability systems, agent-enablement tooling, and production MLOps/LLMOps capabilities. Own features end-to-end, contribute to architecture and design decisions, optimize reliability, scalability, security, and cost, and collaborate with AWS Professional Services, client teams, and junior engineers.