Top Senior Data & Analytics Jobs in Columbus, OH

Designs and builds scalable data platforms and pipelines for scientific, clinical, manufacturing, and process-engineering data. Responsibilities include developing batch and streaming ETL/ELT systems, integrating Databricks, Snowflake, cloud platforms, MES, SCADA, and laboratory systems, and enforcing governance and GxP compliance. The role provides hands-on technical leadership, establishes data engineering standards, and collaborates with scientists, process engineers, and platform teams. It requires three days onsite weekly in Indianapolis and unrestricted U.S. work authorization.

Lead business intelligence strategy across product, clinical, commercial, finance, and engineering teams. Build measurement frameworks, semantic layers, reporting solutions, and visualizations that demonstrate business value and support data-informed decisions. Own the data lifecycle from ideation through client-facing delivery, ensure data governance and integrity, and translate complex datasets into actionable insights. Collaborate on scalable data architecture and apply statistical methods, advanced analytics, and emerging AI-driven BI capabilities.

Leads complex data analytics projects from strategy through completion, delivering predictive models, statistical analyses, dashboards, and actionable insights. Owns data integration, transformation, visualization, experimentation, governance, and ELT quality across Snowflake, DBT, Tableau, and Metabase. Partners with cross-functional stakeholders, mentors analysts, promotes self-service reporting, and communicates findings to leadership. Requires 5–8 years of analytics or business intelligence experience.

Leads Northwest Bank’s enterprise data governance program, including data policies, quality rules, lifecycle management, metadata, master data, stewardship, governance tooling, and remediation. Facilitates Data Working Groups, investigates root causes, manages governance metrics and reporting, demonstrates tools, documents processes, and supports training. Partners across a matrixed organization to ensure data assets meet standards, controls, regulatory requirements, and business needs.

Leads enterprise API governance operations, including API inventory reconciliation, data-quality analysis, KPI/KRI reporting, governance controls, audit support, remediation tracking, and process improvement. Partners with engineering, architecture, security, risk, and technology leadership teams to resolve findings, maintain governance documentation, and present inventory health, compliance, and operational risk insights. Requires advanced analytical, communication, regulatory compliance, and subject-matter expertise.

Establishes and operates North America Operations’ data-governance framework, including ownership, stewardship, quality, metadata, lineage, definitions, and AI governance. Partners with business, data, technology, risk, and compliance teams to resolve data issues, automate controls, improve trust, and embed governance into data products, analytics, and AI solutions. Develops playbooks, training, metrics, and continuous-improvement processes while driving accountability across functions.

Leads the design, development, maintenance, and implementation of complex ETL pipelines across structured and unstructured data sources. Establishes scalable, metadata-driven integration patterns, improves data quality and maintainability, performs root-cause analysis, and supports secure data solutions. Collaborates with stakeholders, maintains ETL platforms and cloud services, advances engineering best practices, and mentors team members.

Design, implement, and mature enterprise data governance frameworks for customer data. Establish standards and processes for data quality, metadata/catalog management, lineage, stewardship, and privacy/consent. Partner cross-functionally to operationalize controls, drive adoption, document standards, manage governance backlog, and support platform enablement and remediation workflows.

The Tableau/BI Developer will manage data, perform data analysis, and create visualizations using BI tools to support risk reduction decisions.

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.