Top Remote Data & Analytics Jobs in Jacksonville, FL

Leads enterprise Business Intelligence strategy, architecture, governance, security, and self-service analytics adoption. Architects solutions across Power BI, Tableau, SAP BusinessObjects, and Databricks; establishes semantic models, data standards, DevOps, CI/CD, and reporting performance practices. Partners with executives and technical teams to modernize analytics platforms, reduce manual reporting, and enable AI-ready decision-making. Mentors BI professionals and drives enterprise data literacy and analytics transformation.

Design, develop, and maintain scalable ETL/ELT data integration pipelines supporting analytics, reporting, and product capabilities. Build ingestion, transformation, validation, and curated data layers; optimize production workflows; document systems; and implement data quality monitoring and testing. Collaborate with implementation, engineering, analytics, and customer success teams to resolve data issues, support onboarding, and ensure reliable, accessible data.

Designs, develops, and maintains scalable ETL/ELT pipelines and data platform capabilities for high-volume healthcare data. Responsibilities include complex SQL development, Airflow orchestration, dbt transformations, data quality frameworks, pipeline monitoring, troubleshooting, performance optimization, and documentation. The role collaborates with Data Operations, Product, Analytics, Data Science, and clinical teams to deliver reliable data for analytics, reporting, product features, and AI/ML initiatives.

Develops business intelligence dashboards, reports, data models, and queries to support data-driven decision-making. Translates business requirements into visualizations, documents requirements and deployment processes, supports existing dashboards and applications, and provides end-user training and technical support. Collaborates with business intelligence and transformation teams to improve member and employee experiences.

Analyzes business performance data and delivers actionable insights for stakeholders and senior leaders. Develops dashboards, scorecards, KPI reports, and recurring brand reporting while ensuring data accuracy and reliability. Partners with sales, marketing, product, and technical teams to translate business needs into analytics solutions. Performs ad hoc analysis, identifies trends and risks, supports executive presentations, and communicates recommendations clearly.

Analyzes e-commerce performance, sales, conversion, traffic, profitability, digital shelf metrics, POS data, consumer behavior, and market trends. Builds executive dashboards and recurring reports, conducts forecasting and ad hoc analyses, and translates insights into recommendations for marketing, merchandising, product development, and channel strategy. Partners with cross-functional stakeholders to identify growth opportunities, improve processes, and support strategic business decisions.

Analyzes customer experience, survey, operational, CRM, ERP, support, and financial data to build unified customer views and actionable insights. Responsibilities include cohort analysis, segmentation, predictive modeling, revenue attribution, CX dashboards, reporting automation, and closed-loop action tracking. The role partners with IT, data teams, Finance, and business stakeholders to improve data quality and translate complex analyses into executive recommendations supporting retention, expansion, and customer experience improvements.

Architect and lead enterprise data platforms, pipelines, and infrastructure using Spark, Databricks, and cloud technologies. Build scalable data models and dimensional schemas, establish governance and data quality frameworks, optimize performance and reliability, and implement monitoring. Partner with stakeholders to translate requirements into technical solutions, lead design reviews, mentor engineers, contribute to platform strategy, troubleshoot complex failures, and support hiring and team development.

Designs and optimizes scalable data platforms, architectures, and production pipelines supporting AI and machine learning. Responsibilities include Databricks Lakehouse development, batch and real-time processing, data governance, security, monitoring, performance tuning, infrastructure planning, and collaboration with DevOps, MLOps, and cross-functional teams. The role serves as the AI team’s data engineering subject matter expert and ensures reliable, secure, cost-effective data solutions.

Teaches online undergraduate and graduate data analytics courses, develops syllabi and lesson plans, prepares course materials, facilitates discussions, evaluates student work, provides feedback, and integrates responsible AI practices. The role requires maintaining course alignment with institutional objectives, supporting diverse learners, participating in faculty training, and applying current analytics methods, tools, and ethical data practices.

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.

Conduct product analytics for MoneyGram’s digital money transfer products. Analyze customer behavior, product performance, experiments, feature releases, and cohort metrics to guide product strategy and growth. Build insights and reporting, collaborate with Product, Engineering, Marketing, Finance, and international teams, and improve analytics platforms, automation, and visualization processes. Translate complex findings into actionable recommendations for technical and non-technical stakeholders.

Owns data-driven analysis supporting company-wide decision-making across customer, product, partner, and financial performance. The role translates ambiguous business questions into actionable recommendations, develops metrics and analytical frameworks, builds data models, dashboards, and scalable analytical solutions, and partners with stakeholders and analytics engineering. It requires advanced SQL, data transformation, business intelligence tooling, strong communication, and experience analyzing B2B SaaS businesses.