Top Senior Data & Analytics Jobs in Columbus, OH

Lead marketing analytics across channel, campaign, cohort, and funnel performance. Build dashboards, reporting, AI-enabled analytical workflows, and data models that support marketing decisions. Conduct ad hoc analyses, evaluate attribution and incrementality, monitor data quality, and translate complex findings into executive recommendations. Partner with marketing and marketing science teams, influence strategic decisions, establish analytical standards, and mentor analysts.

Senior Database Administrator responsible for optimizing MySQL and AWS Aurora query performance, indexes, execution plans, stored procedures, and database architecture. Supports SQL Server and AWS RDS environments, cloud migrations, schema refactoring, data modeling, maintenance, backups, and operational tuning. Collaborates with developers and QA teams on database code reviews and mentors engineers on query optimization. The role requires extensive DBA experience, cloud database migration expertise, and strong relational data modeling skills.

Leads the design, development, optimization, and migration of modern data platforms in Snowflake. Builds pipelines with dbt, Python, and cloud services; gathers client requirements; creates solution designs and project plans; advises on Snowflake performance, cost, security, and workload management; integrates BI, governance, and AI/ML tools; contributes to accelerators and mentors junior engineers. The role is remote, client-facing, consultative, and focused primarily on technical delivery rather than sales.

Build and operate batch and streaming data pipelines, ETL/ELT workflows, data warehouses, dimensional models, and reusable data services. Improve reliability, performance, quality, and cost efficiency through monitoring, testing, automation, and incident response. Partner with analytics, data science, product, business, platform, and infrastructure teams to deliver production data solutions and roadmap initiatives. Apply AI-assisted tools responsibly to development, testing, documentation, and troubleshooting.

Manages Finance analytics engineering and automation, building governed Snowflake and SQL data products, consumption layers, reconciliations, controls, workflows, and integrations. Partners with FP&A, Data Engineering, and business teams to translate Finance requirements into reliable technical solutions. Leads lineage analysis, testing, monitoring, documentation, AI-assisted workflows, production support, and team development while maintaining clear ownership between Finance and enterprise data teams.

Lead the architecture and hands-on development of an AI-enabled data migration platform for legal software. Own extraction, transformation, orchestration, data quality, observability, and scalable go-live workflows. Partner with product management to define roadmap priorities, lead a focused engineering team, make architectural decisions, contribute code, and apply AI to migration assessment, mapping, validation, and automation.

Build and maintain dbt and semantic data models in Snowflake, develop ingestion and transformation pipelines, define trusted product metrics, and improve data collection. Partner with Product and Engineering to support experimentation and feature analysis. Establish data quality testing, documentation, HIPAA-aware access controls, and compliance practices. Use and validate AI-generated code and Snowflake Cortex outputs while raising technical standards across the team.

Build customer health scores, churn and expansion analytics, retention dashboards, automated alerts, and executive reports. Maintain integrations among databases, CRM, and BI tools while improving data quality and standardizing reporting. Lead AI adoption for analytics, validate generated insights, and enable customer-facing teams to make informed retention and expansion decisions. Requires strong BI, logistics or supply chain analytics, dashboarding, data integration, communication, and customer-focused skills.

Leads the design, development, and optimization of scalable data pipelines and analytics platforms. Builds ETL/ELT workflows using Databricks and Spark, integrates and transforms source data into curated models, manages SQL Server data, and maintains documentation and lineage. Collaborates with product, analytics, and engineering teams to deliver reliable data solutions. Applies responsible AI practices and delivers projects independently within established timelines.

Develop customer analytics that improve retention, growth, adoption, and operational performance. Build and maintain BI dashboards, customer health metrics, churn-risk reporting, and predictive models. Partner with Client Success, Product, Sales, and Operations to translate complex findings into actionable recommendations. The role also owns data quality, governance, reporting automation, workflow improvements, and stakeholder communication.