Top Senior Data & Analytics Jobs in Columbus, OH

Designs, develops, and optimizes enterprise data pipelines and platforms using Snowflake, integrating Oracle Fusion, on-premises databases, and cloud applications. Applies data quality, governance, security, and performance practices while supporting Power BI, AI, and machine learning use cases. Partners with business and technical stakeholders, leads data migrations, translates requirements into sustainable solutions, mentors junior engineers, and guides engineering standards.

Designs and maintains executive dashboards, reports, semantic models, and automated analytics solutions using Power BI. Defines enterprise KPIs, data standards, and business rules while integrating data from ERP, CRM, manufacturing, SQL, and cloud systems. Partners cross-functionally with senior leaders to deliver insights, improve data quality, support master data management, and enable scalable self-service analytics and data-driven decision-making.

Leads end-to-end data architecture, engineering pipelines, semantic-layer development, data quality, monitoring, and platform operations. Manages sprint planning, releases, DevOps metrics, project delivery, and stakeholder communication. Establishes MLOps and machine-learning platform capabilities, mentors data engineers, and ensures reliable, well-documented data solutions that support organizational reporting and analytics needs.

Develop and manage enterprise Power BI dashboards, semantic models, data integrations, and automated reporting for global commercial operations. Analyze Salesforce and other business data using SQL and Python, support sales performance, territories, forecasting, compensation, and executive decision-making. Own reporting reliability, data quality, governance, troubleshooting, and documentation while partnering with Sales, Finance, Marketing, IT, and commercial leadership.

Optimize and administer SQL Server databases supporting multi-terabyte healthcare claims data. Responsibilities include tuning T-SQL, execution plans, indexing, partitioning, statistics, tempdb, memory, backups, high availability, and database monitoring. The role develops stored procedures and data structures, identifies claims overpayments, automates data mining processes, investigates root causes, and mentors analysts. Collaboration with infrastructure and business teams is required, along with ownership of small projects and performance improvements.

Own experimentation analytics across Product and Marketing, including A/B and multivariate test design, causal inference, statistical analysis, dashboards, dbt models, and data infrastructure. Translate results into business recommendations, improve experimentation frameworks and self-service reporting, partner with engineering on instrumentation, mentor analysts, and manage the analytics roadmap.

Build and govern clinical analytics datasets, SQL transformations, data marts, dashboards, and reporting solutions for clinical quality, patient safety, outcomes, regulatory, and research initiatives. Partner with clinicians, executives, researchers, and enterprise data teams to define metrics, ensure data integrity, implement testing and governance frameworks, and deliver trusted executive, board, regulatory, and clinician-facing insights using modern cloud data platforms.

Leads analytics strategy and delivery by partnering with business stakeholders, customers, and data engineering teams. Defines and prioritizes analytical roadmaps and backlogs, translates business needs into technical requirements, supports data governance, coordinates development, communicates progress, and manages user acceptance testing. The role promotes data-driven decision-making and ensures analytical solutions deliver sustainable business value.

Leads business analytics engagements, translating stakeholder needs into data requirements, models, dashboards, forecasts, statistical analyses, and actionable recommendations. Performs data exploration, querying, modeling, and visualization across large datasets; supports data governance, quality, security, and stewardship. Mentors analysts, communicates insights to leaders, collaborates with enterprise data teams, and identifies opportunities to apply machine learning in business decision-making.

Build governed, reusable Data 360 products and scalable transformation pipelines using SQL, Python, dbt, and Snowflake. Establish dimensional models, semantic layers, trusted metrics, data quality controls, lineage, and governance for clinical, laboratory, operational, and commercial data. Ensure PHI and genomic data compliance while integrating AI-native engineering practices. Collaborate with cross-functional stakeholders, lead architecture decisions, validate data products, resolve complex data issues, and mentor engineers.