Top Senior Analytics Jobs in Columbus, OH

Lead pricing analytics for merchant/platform deals and international market expansion. Define pricing strategy, run economic analyses, design and test pricing constructs, and collaborate with product, partnerships, credit, finance, capital markets, and engineering to optimize portfolio performance.

Lead Databricks-based enterprise data and analytics modernization programs. Define future-state architecture, drive platform modernization, ensure security, scalability, cost optimization, and mentor teams while delivering AI-ready data platforms and governance.

The Senior Analytics Engineer will develop data pipelines, build models, and create dashboards to provide actionable insights for various teams. The role requires collaboration with multiple stakeholders to meet analytical needs and ensure data governance.

Design, build, and optimize modular dbt pipelines and data models; translate ambiguous product requirements into production-grade data assets; diagnose query performance and lower warehouse compute costs (including migration to Snowflake); enforce code hygiene, data security, testing, and peer review; mentor junior engineers and adopt AI-assisted development tools to speed test generation and legacy discovery.

Lead Retail GTM analytics and territory operations: build reporting, automate workflows, design territory models, manage data quality/enrichment, and deliver decision-support tools across Salesforce, Snowflake, and Sigma to scale sales coverage and drive growth.

Design, build, and maintain scalable dimensional data models, semantic layer, and production transformation pipelines. Collaborate with Data Engineering, Data Science, BI, DevOps, and Product to enable AI-ready data, ensure data quality and governance, support ML feature delivery, and coach analytics team members for robust, production-ready data products.

Lead technical design and architecture for analytics engineering: build and govern the semantic/metrics layer, optimize dbt and Snowflake for performance and AI use cases, mentor engineers, partner with Data Science and Engineering, drive data quality, CI/CD, observability, and deployment of third-party data and emerging tooling to support analytics, ML, and agent-based products.

Lead and grow a team of analytics engineers while remaining hands-on with SQL, dbt, and Snowflake. Own roadmap and semantic layer development, build trusted, governed data products, partner with cross-functional stakeholders, champion data quality and observability, and hire and coach engineering talent to deliver scalable analytics and AI-ready foundations.

Design and build Toast’s enterprise analytics layer and AI-ready semantic layer in the data warehouse. Collaborate with domain teams and data engineering to implement hub-and-spoke architecture, define complex business logic in SQL, support scalability, partner with stakeholders, and provide technical mentorship.

Lead retail analytics to identify growth and efficiency opportunities, build strategic recommendations (store footprint, pricing, omnichannel), conduct market/competitive research, drive cross-functional initiatives, and deliver executive-ready analyses and frameworks to inform retail and digital strategy.

Lead building a data- and AI-enabled growth engine to improve pipeline quality and visibility. Define data governance, segmentation, scoring, and KPIs; operationalize demand-generation campaigns and tooling; prototype AI-driven automation and reporting; partner with vendors and sales/marketing to measure and improve pipeline conversion and ROI.

Owner of the analytics foundation: design and maintain BigQuery/dbt models, pipelines, and Looker Studio reporting; build AI workflows and web apps on GCP; integrate marketing, e-commerce, and fulfillment data; ensure GCP ops, security, and reliability; use AI-assisted tools daily and collaborate with business and client stakeholders.

Lead end-to-end COGS and gross margin analysis for hardware and software products, model cost-saving scenarios, answer ambiguous executive questions, partner with data engineering/finance/product, build reliable datasets and analytical frameworks, and present recommendations to C-suite stakeholders.

Lead client-facing marketing analytics projects using SAS and statistical methods. Perform marketing mix modeling, multi-channel attribution, digital analytics, pricing/promotion analysis, demand forecasting, and mentor a team while traveling extensively to client sites.

The Senior Analytics Engineer will design and implement scalable data solutions for Finance Analytics, reconcile data accuracy, and collaborate across teams to enhance financial datasets and reporting workflows.

Lead a team in delivering data-driven insights for underwriting and risk selection, managing projects and fostering relationships across business units.

Lead global operations reporting and governance by consolidating data across 30+ plants. Own KPI definitions, data integrity, Power BI dashboards, SQL data transformations, Oracle ERP integrations, and support AI/ML pilots to provide executive insights and drive continuous improvement across supply chain and manufacturing operations.

Lead onboarding, mapping, and validation for a Customer Data Hub: write user stories and acceptance criteria, define mastering/transformation logic, perform data lineage and reconciliation, validate integrations and outcomes, support production incidents, create runbooks and documentation, and partner with product, engineering, QA, and governance teams to enable reliable customer data for applications and analytics.

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.

Lead and build a product analytics function: define KPI framework, instrumentation, and self-serve analytics using Pendo and BI tools. Partner cross-functionally to measure product performance, surface insights, influence roadmap and embed AI-powered analytics into product lifecycle.

Develop and support analytics solutions by extracting and prepping data, building data models, dashboards, and integrated analytics. Partner with business and IT to design EDW/Data Lake, ensure data quality and governance, automate monitoring, and introduce predictive/data science elements. Promote BI best practices and sustain user-facing analytics performance.

Lead development of Marriott's cloud data platform, build and own large-scale ETL pipelines on AWS and Snowflake, mentor engineers, manage service provider deliverables, ensure governance, data quality, deployment and production support, and research emerging AI/ML capabilities.

Design, build, and maintain production ETL/ELT pipelines, analytics-ready data models, and cloud data infrastructure. Improve pipeline performance, data quality, governance, and migrate legacy systems to modern platforms. Collaborate with stakeholders to translate business requirements into reliable data products for project, financial, and operational analytics.

Design and implement end-to-end data solutions on Microsoft Fabric and Azure for insurance datasets. Build ingestion pipelines (batch, streaming, API), Lakehouse architectures, and data models. Enforce governance, security, compliance, and cost/performance optimizations while guiding engineers and stakeholders on architectural best practices.

As a Senior Analyst, you will develop data-driven solutions in collaboration with operations teams and deliver insights through reports and dashboards to improve patient outcomes.