Top Data & Analytics Jobs in Jacksonville, FL

Design, build, and maintain scalable data pipelines and models using Databricks, dbt, and PostgreSQL. Develop AWS-based data solutions (Redshift, RDS, S3, Glue, Lambda, DMS), implement ETL/transforms in Python and Java, use Terraform for IaC, monitor with CloudWatch and Splunk, perform code reviews, and collaborate with stakeholders in agile teams to deliver reliable data systems.

The Head of Data will build and manage a centralized data hub, integrating infrastructure and governance to support AI transformation, while driving measurable business value through strategic data initiatives and strong team leadership.

Lead revenue forecasting, planning, and executive reporting across new, renewal, and expansion revenue. Manage and grow a revenue insights team while owning pre-sales analytics, forecast methodology, capacity and quota planning, and performance narratives. Build pipeline and forecast reporting, track conversion/velocity metrics, surface risks early, and apply AI to improve forecasting, anomaly detection, and automated insights.

Design, develop, and maintain Snowflake-backed semantic models and Power BI reports; build SQL queries, functions, and stored procedures; use AI-assisted tooling (Claude, MCP) to accelerate BI development; manage work in Azure DevOps, version control with GitHub; ensure QA, documentation, stakeholder communication, and mentor fellow developers.

Lead measurement and analysis of client experience across NPS, CSAT, churn, renewals, support, onboarding, and account health. Identify systemic risks, design leading indicators and health scores, build executive dashboards, quantify financial impact, influence cross-functional priorities, support journey improvement pilots, and synthesize qualitative and quantitative client insights for organizational action.

Lead design and delivery of scalable data lakes, warehouses, and pipelines. Define governance, quality, monitoring, and CI/CD. Build real-time streaming systems and production AI/ML data flows (embeddings, vector stores, RAG, feature stores). Mentor engineers, set platform strategy, and drive data platform modernization.

Responsible for creating and maintaining technical documentation for developers, ensuring clarity and effectiveness in conveying product capabilities and usage. Collaborate with engineering and growth teams to enhance resources while gathering feedback for continuous improvement.

Build, maintain, and optimize cloud data pipelines and dbt models; design Airflow DAGs; implement dimensional models and BI dashboards; integrate healthcare data with HIPAA-compliant practices; contribute to RAG pipelines and MLOps workflows; review contractor code, monitor data quality, and document designs following governance standards.

Build and operate data-intensive web products and APIs, extend high-throughput ETL pipelines and scrapers, ensure reliability/observability, design self-scaling services, participate in code review, and collaborate across product, data, and infrastructure teams to meet production SLAs.

The role involves managing actuarial modeling for Retirement Plans, ensuring quality of outputs, overseeing BAU execution, and training junior staff.