Top Remote Analysis Reporting Jobs in Jacksonville, FL

Designs and maintains scalable data solutions on Palantir Foundry for FAA enterprise platforms. Responsibilities include modeling data with Palantir Ontology, developing data objects, actions, applications, workflows, pipelines, and AI integrations, while supporting governance, security, APIs, documentation, training, users, and stakeholders.

Leads data strategy and analytics for the Risk/Credit team, translating complex datasets into insights for Credit, Operations, Marketing, Product, and Finance. Responsibilities include automating Python/R workflows, building Tableau dashboards, partnering with Data Engineering on Databricks workflows, conducting strategic analyses, monitoring data quality, presenting recommendations to leadership, and documenting analytical methodologies. The role requires strong SQL, cloud data warehouse, visualization, analytics programming, distributed computing, and version-control expertise.

Lead data architecture consulting engagements, pursuit teams, client workshops, proofs of concept, and complex solution delivery. Design modern data architectures, integrate third-party platforms, create implementation roadmaps, and translate technical concepts for executive and technical audiences. Manage globally distributed teams, provide mentorship and thought leadership, support sales pursuits, and advise clients on data governance, quality, cataloging, lineage, master data management, cloud platforms, modernization, scalability, security, and AI-enabled solutions.

Lead the architecture and implementation of enterprise-scale GCP data ecosystems, including PB-scale platforms and AWS-to-GCP migrations. Establish data platform roadmaps, self-service architectures, governance, security, quality, and Infrastructure as Code standards. Architect solutions using GCP data, analytics, AI, streaming, and containerization technologies. Lead cross-functional engineering teams, mentor staff, advise executives, manage technical risks, and communicate the business value of data initiatives.

Own end-to-end data platform architecture across ingestion, lakehouse, warehouse, transformation, modeling, governance, and analytics delivery. Build pipelines, Spark and SQL transformations, data models, and production code. Design Databricks or Microsoft Fabric lakehouses, implement Delta Lake and medallion architecture, establish access controls and governance, and integrate databases, SaaS applications, APIs, files, and legacy systems. Evaluate platform choices based on client workloads, licensing, skills, and cost.

Design, build, and support enterprise BI solutions including reports, dashboards, ETL/ELT, data marts, governed datasets and production support. Translate business requirements into technical designs, perform complex data analysis and root-cause investigations, document lineage and runbooks, optimize solutions, enforce data governance, and provide technical leadership or mentorship for large-scale initiatives.

Lead the firm’s analytics strategy, roadmap, and growing analyst team. Partner with executives and law firm operations leaders to define KPIs, evaluate performance, identify bottlenecks, build forecasting and predictive capabilities, and translate data into business actions. Guide SQL, Python/R, statistical modeling, visualization, data quality, and analytics infrastructure standards while partnering with technology and data engineering teams to embed insights into operational workflows.

Design and develop scalable analytics tools, dashboards, evaluation frameworks, and observability systems for promotional media and marketing workflows. Partner with machine learning engineers, data scientists, product managers, and business stakeholders to monitor algorithm adoption, pipeline health, performance drift, and SLA adherence. Translate ambiguous creative and quality requirements into measurable objectives, improve recommendation and asset-generation models, and use data insights to guide business decisions.

Own end-to-end marketing measurement from campaign tracking through pipeline and revenue. Define tagging, event tracking, dataLayer, UTM, taxonomy, CRM, and marketing automation standards; ensure clean data handoffs, routing, attribution, and reporting. Lead QA and troubleshoot discrepancies across technical and operational systems. Partner with marketing, sales, analytics, engineering, and operations teams to establish measurement frameworks, documentation, data models, and repeatable processes leadership can trust.

Supports fundraising by managing prospect portfolios and pipelines, tracking moves management activity, conducting prospect research, and providing analysis and recommendations to philanthropy officers. Maintains accurate donor records and databases, develops reliable reporting, facilitates portfolio reviews, and identifies donor engagement opportunities using demographic, philanthropic, and engagement data.