Top Data & Analytics Jobs in Jacksonville, FL

Leads end-to-end marketing analytics for small business acquisition campaigns, including opportunity sizing, targeting, experimentation, performance reporting, profitability, and ROI measurement. Partners with Marketing, Finance, Modeling, and Data teams to guide investment decisions and improve measurement rigor. Owns stakeholder delivery, data requirements, analytic frameworks, controls, and auditability while coaching junior analysts and translating complex findings into clear recommendations for senior audiences.

Lead design and implementation of data architecture for healthcare systems, influence stakeholders, mentor teams, ensure regulatory compliance, enable data integration and transformation, and apply AI techniques to improve healthcare operations and reporting.

Support asset-level data intake, validation, and exception triage for private markets. Ensure data quality and standardization, perform trend analysis to inform product and process improvements, coordinate onshore/offshore delivery, document operational logic, and collaborate with Product, Data, and Engineering teams to improve workflows and client reporting.

Provides data analytics consulting for enterprise clients using Dynatrace observability, digital experience monitoring, and business analytics data. Manages client relationships, performs ad hoc analysis, creates reports and dashboards, presents findings to technical and executive audiences, configures tools, trains users, and influences product improvements. The role translates complex performance and engagement data into strategies that improve digital experiences and business outcomes.

Leads Toast’s analytics engineering function, owning enterprise data architecture, modeling strategy, analytics-layer development, and AI-ready semantic-layer vision. Builds and manages a team of analytics engineers, establishes roadmaps, partners with data engineering and business leaders, and drives scalable, governed data solutions across domains. Requires expertise in data modeling, dbt, SQL, stakeholder alignment, and people leadership.

Lead marketing analytics for customer upsell, lifecycle, activation, adoption, and retention initiatives. Analyze customer data and campaign performance, identify trends and growth opportunities, develop recommendations, and estimate business impact. Collaborate with Marketing, Sales, Finance, Analytics, and Web teams to improve customer experiences, attribution frameworks, dashboards, and self-service growth strategies.

Lead and grow a global data engineering team while establishing foundational data platforms and engineering standards. Design and oversee GCP-based pipelines, medallion data models, DataOps, monitoring, SLAs, CI/CD, governance, and data quality practices. Drive AI adoption across engineering workflows and build reliable, AI-ready data. Partner with business and technology stakeholders to prioritize roadmaps, deliver scalable solutions, and support data democratization.

Architects, deploys, and operates scalable data platform infrastructure supporting analytics. Responsibilities include administering Airflow and Superset, managing Terraform infrastructure, building CI/CD pipelines, enforcing security and compliance, developing DBT data models, cataloging assets in OpenMetadata, writing Python automation, and mentoring engineers. The role requires extensive infrastructure and data engineering experience across cloud platforms, containers, data security, and workflow orchestration.

Own implementation, maintenance, and optimization of client eligibility and claims data feeds. Analyze feed performance, troubleshoot discrepancies, produce error reports, test integrations with external partners, and improve internal tools, documentation, and processes to increase automation and reliability.

Lead programmatic analytics for clients and internal teams by analyzing campaign and model performance, designing tests, developing measurement solutions, recommending optimizations, and presenting actionable insights. Partner with Sales, Customer Success, Product, Engineering, and clients to align marketing strategies, reporting requirements, and optimization efforts with business goals.

Leads the strategy, architecture, implementation, and evolution of enterprise analytics platforms. Responsibilities include designing scalable data platforms, integrating digital and enterprise data, establishing governance and security standards, optimizing analytics and BI capabilities, evaluating cloud technologies, managing platform performance and risks, and mentoring technical teams. The role also requires close collaboration with executives, clients, Product, Engineering, Data Science, Marketing, and business stakeholders.