Top Remote Data & Analytics Jobs in Palm Bay, FL

Designs and maintains data warehouse infrastructure, semantic and dimensional models, metrics layers, dashboards, reporting, and secure data pipelines. Builds governed self-service analytics in Sigma, Power BI, and Databricks; defines KPIs and data standards; implements row-level security and Entra ID controls; supports data quality, observability, AI/ML use cases, and BI adoption. Collaborates with technical and business stakeholders in an Agile-Scrum environment.

Supports GIS data creation, editing, cleanup, maintenance, QA/QC, standardization, and map product development for NASA Johnson Space Center facilities and utilities. Collaborates with field surveyors and external parties to transform and integrate data, creates story maps and dashboards, and edits data in a branch version environment. This temporary role requires three years of GIS experience, a relevant bachelor’s degree or equivalent experience, and U.S. continental location.

Lead a small analytics team (staff data scientist + two analysts) to deliver curriculum, product, and program insights. Split time between people management (60-70%) and hands-on analysis (30-40%), advance experimentation and measurement, build AI/LLM-driven agentic workflows, manage sprints and cross-functional stakeholder relationships, and drive analytics that inform curriculum, product, and intervention strategies.

Design and build PerfectServe’s unified cloud data platform, including ingestion pipelines, integrations, data models, metrics, and consumer-facing data layers. Establish architecture, engineering, quality, and testing standards; enable safe extraction from production systems; partner with data users; and mentor data engineers. The role requires substantial cloud data platform experience, deep SQL, warehouse expertise, ELT, change-data-capture, AWS, modeling, orchestration, and data quality skills.

Designs, builds, and maintains enterprise data pipelines, ETL processes, integrations, data infrastructure, and complex data models. The role supports analytics partners, develops scalable data warehouse solutions, tunes SQL and databases, troubleshoots production issues, and collaborates with architects, analysts, developers, and stakeholders. Responsibilities include end-to-end project delivery, data modeling, big data engineering, production support, agile planning, and mentoring team members.

This role involves writing user stories, supporting agile team processes, and driving customer discovery to enhance technology solutions for clients.

Conducts research and analysis of workload and operational data, creates customer-focused reports, identifies trends and reporting issues, and provides insights and recommendations to improve efficiency. Supports contract teams, management, outreach, and training while handling confidential information and meeting strict deadlines. The role requires strong analytical, organizational, communication, and computer skills, including Access, Excel, reporting extracts, and Web Intelligence.

Leads the design, development, and maintenance of scalable AWS data platforms, pipelines, ETL/ELT workflows, data models, and orchestration systems. Uses Python, PySpark, SQL, dbt, AWS services, modern lakehouse technologies, and CI/CD practices to deliver secure federal data solutions. Responsibilities include platform modernization, performance optimization, AI-enabled data integration, compliance support, technical mentoring, architecture discussions, and cross-functional Agile collaboration.

Supports client analytics and business-systems engagements by preparing, validating, mapping, and analyzing data; configuring and testing ERP systems; creating Tableau visualizations and reports; documenting processes; supporting data integration; and communicating with stakeholders. The role works under Lead Analyst guidance while developing ERP, consulting, and account-facing expertise.

Leads scalable data model and pipeline design, dbt development, testing, CI/CD, and analytics engineering implementations. Partners with analysts, engineers, and stakeholders to translate business needs into reliable models and semantic layers. Advises on data architecture, governance, quality, performance, and long-term scalability while mentoring peers and contributing to shared tooling, standards, and frameworks.