Top Remote Data & Analytics Jobs in Jacksonville, FL

The Director of Data owns the company’s data platform, governed metrics, client identity resolution, data quality, privacy controls, and AI-ready datasets. This leader manages the data team, establishes governance and operating standards, oversees warehouse and pipeline architecture, and ensures reliable data for Finance, leadership, products, and ML/LLM systems. The role requires hands-on technical leadership, roadmap ownership, stakeholder communication, and accountability for data reliability, lineage, security, and platform costs.

Analyze credit portfolio and loan performance, forecast losses, identify risks and opportunities, and develop strategies to improve credit outcomes and origination volume. Use SQL, Python, dashboards, and visualizations to deliver actionable insights. Present recommendations to stakeholders and senior leaders while managing analytical projects, A/B tests, roadmaps, and business priorities independently.

Lead data engineering strategy and develop enterprise data lake solutions on AWS. Build data pipelines using AWS data integration, engineering, and analytics resources, develop API services with FastAPI or Flask, optimize engineering practices, create long-term data plans, and represent the team in executive meetings.

Lead the architecture and hands-on development of an AI-enabled data migration platform for legal software. Own extraction, transformation, orchestration, data quality, observability, and scalable go-live workflows. Partner with product management to define roadmap priorities, lead a focused engineering team, make architectural decisions, contribute code, and apply AI to migration assessment, mapping, validation, and automation.

Provides senior SQL Server database engineering and DBA services for client environments. Responsibilities include performance tuning, cloud database architecture, high availability and disaster recovery, capacity planning, automation, monitoring, migrations, deployment scripting, root-cause analysis, and client advisory services across AWS and Azure.

Develops and maintains core backend systems, databases, data workflows, integrations, and SQL solutions supporting federal healthcare TPA services. Responsibilities include database design, stored procedures, performance tuning, ETL/ELT, APIs, EDI, cloud data technologies, modernization, interoperability, and secure handling of healthcare data. Collaborates with architects, analysts, QA, operational teams, data engineers, and vendors. The role is remote with up to 10% travel and requires an MBI (T2) background investigation.

Develops and implements business process improvements and system changes. Gathers stakeholder requirements, analyzes workflows and business impacts, reviews technical deliverables, prepares business cases, and recommends solutions. Provides training, change communications, post-implementation support, and process improvement strategies. Requires strong research, analytics, financial and risk analysis, Excel, workflow modeling, project planning, communication, and stakeholder-management skills.

Leads enterprise data governance and stewardship in a federated operating model. Responsibilities include onboarding data domains, implementing metadata and business glossary practices, managing governance platforms, driving stewardship adoption, establishing policies and workflows, monitoring governance KPIs, and partnering with business, technology, security, privacy, legal, and compliance teams. The role also oversees managed service providers and junior governance resources while enabling data quality, compliance, analytics, and AI readiness.

Build and own scalable data architecture, canonical data models, configurable source integrations, and reliable pipelines for AI-driven financial intelligence. Use SQL, Python, dbt, cloud data warehouses, and orchestration tools to deliver idempotent, auditable data workflows. Establish lineage, data contracts, quality controls, and schema evolution practices. Lead architecture reviews, mentor distributed data engineers, and support customer-hosted multi-cloud deployments with strict tenant isolation and traceability.

Build and maintain dbt and semantic data models in Snowflake, develop ingestion and transformation pipelines, define trusted product metrics, and improve data collection. Partner with Product and Engineering to support experimentation and feature analysis. Establish data quality testing, documentation, HIPAA-aware access controls, and compliance practices. Use and validate AI-generated code and Snowflake Cortex outputs while raising technical standards across the team.