Top Data & Analytics Jobs in Jacksonville, FL

Performs data engineering operations including SQL scripting, ETL and data validation, query optimization, data analysis, dashboard maintenance, task-result validation, and troubleshooting with engineering and DBA teams. Ensures data integrity and compliance, manages ticket-based assignments, and supports data production and implementations. The role may require after-hours or weekend support and includes preferred experience with network security platforms, certificate management, and automation scripting.

Designs, develops, and sustains cloud-based data analytics infrastructure and ETL pipelines. Manages data retention, curation, cataloging, schemas, and automation across AWS, Elasticsearch, and Google Analytics platforms. Creates visualizations and reports using Kibana, AWS QuickSight, and Google Analytics 4. Supports cloud-native architecture, infrastructure automation, DevOps, monitoring, troubleshooting, bug fixes, and customer support.

Collects and analyzes data from project, financial, maintenance, and field systems; builds KPI dashboards and recurring reports; identifies trends, risks, and opportunities; supports budgeting and forecasting; validates data with project and operations teams; and communicates actionable insights to leadership while improving reporting processes.

Collects, organizes, cleans, and analyzes business data; reviews data accuracy and completeness; prepares reports, dashboards, and summaries; identifies trends supporting business decisions; and maintains spreadsheets and databases. The role is fully remote, includes paid training, and requires strong communication, organization, attention to detail, and independent work capability.

Leads integration of healthcare payer feeds and internal enterprise data into WellBe’s data platforms. Responsibilities include data mapping, transformation, validation, normalization, quality monitoring, governance, metadata and lineage management, requirements gathering, and supporting ingestion pipeline delivery. The role partners with engineering and analytics teams, serves as a subject matter expert, and ensures reliable data for value-based care, reporting, and operational use cases.

Leads the architecture, implementation, and evolution of enterprise data platforms, including Master Data Management, data lakes, lakehouses, and cloud data services. Manages data engineers and developers, establishes engineering standards, oversees Azure-based integrations and pipelines, and owns data applications, databases, security, governance, and production support. The role also directs technical strategy, manages multiple initiatives, and communicates architecture and delivery plans to stakeholders.

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 Forward Deployed Data Engineer will manage AI-automated data platform migration projects, ensuring timely delivery and communication with clients while utilizing proprietary tools.

Analyze insurance product and portfolio performance, build dashboards and reporting tools, validate data, and translate complex insurance questions into actionable recommendations. The role supports rate revisions, state expansion, product development, and profitable growth while partnering with Product, Engineering, Data, Underwriting, Compliance, and other teams. It also uses SQL, business intelligence platforms, and AI tools such as Claude to improve workflows and decision-making.

Owns lead and account data quality across the sales pipeline. Responsibilities include deduplicating and enriching CRM records, defining lead quality and routing standards, maintaining account structures, resolving data escalations, evaluating enrichment vendors, and assessing AI for quality assurance and anomaly detection. Partners with sales leadership to build scalable workflows and validation processes using CRM tools, SQL, spreadsheets, and potentially Python.