Top Remote Data & Analytics Jobs in Orlando, FL

Leads PBM data integration delivery across claims, eligibility, accumulator, and encounter systems. Profiles and validates data, writes advanced SQL, resolves reconciliation discrepancies, investigates production issues, and partners with engineering on scalable healthcare integration architecture. Owns timelines, risks, vendor dependencies, testing, UAT, migration, rollback planning, executive reporting, and post-deployment support. Requires deep PBM claims-processing expertise, data architecture experience, and hands-on knowledge of ETL, secure file transfer, job scheduling, and healthcare data standards.

Develop and enhance trade and commercial reporting solutions using Snowflake, Tableau, and related BI tools. Modernize manual and legacy reporting workflows into automated dashboards and scalable analytical solutions. Translate queries and business rules across data platforms, validate reporting accuracy, investigate discrepancies, document workflows, and partner with commercial and senior stakeholders to deliver actionable insights.

Analyze public spending datasets, collaborate with the Deputy Policy Director, and develop comparative research projects that reveal insights about government waste and public policy outcomes. The role involves brainstorming data-driven story ideas, drawing conclusions from proprietary datasets, and pitching findings in a fully remote environment.

Owns enterprise data architecture for Raytheon’s SAP ECC-to-S/4HANA transformation. Designs canonical data models, integration patterns, bridge reporting, semantic layers, and cross-system analytics for finance, supply chain, and other domains. Guides SAP Analytics Cloud, Snowflake, Business Data Cloud, and BODS solutions; establishes governance, standards, lineage, and observability. Creates TOGAF-aligned architecture artifacts, reviews delivery solutions, and coaches technical teams throughout the migration lifecycle.

Design, build, and deploy production-grade data pipelines, analytics platforms, and Generative AI applications on Databricks. Lead enterprise migrations from legacy data platforms, architect cloud-native solutions, implement RAG and ML pipelines, and advise executive client stakeholders. Drive Databricks adoption and account growth by identifying new use cases, while mentoring engineers and contributing reusable delivery accelerators.

Evaluate search engine results and provide feedback on text, audio, images, and videos to improve AI and online search experiences. Conduct online research, assess relevance and significance, maintain quality and accuracy standards, and complete assignments independently from a home office. The role requires English and Spanish proficiency, flexible part-time availability, completion of training and testing, and use of a smartphone, computer, reliable internet, and antivirus software.

Builds and maintains scalable data pipelines and reusable datasets in Databricks. Ingests, validates, transforms, and models structured and unstructured data using Python, PySpark, and SQL. Integrates warehouse and cloud analytics systems, supports Tableau and Spotfire reporting, improves reliability and performance, and implements testing, monitoring, documentation, and CI/CD. Collaborates with technical and business stakeholders while providing technical guidance, code reviews, and mentorship.

Own the analytics engineering roadmap, architecture, and production data models. Build and optimize dbt models using SQL, Python, and Databricks; establish dimensional models, governed metrics, testing, documentation, lineage, monitoring, and CI/CD practices. Partner with data engineering, analysts, BI developers, and stakeholders to deliver reliable analytics products, improve performance and cost efficiency, investigate data quality issues, and mentor team members.

Build and operate a large-scale enterprise data platform spanning batch and streaming processing, lakehouse storage, Kafka infrastructure, APIs, observability, and agentic MCP interfaces. Develop reusable ingestion and data-quality frameworks, improve scalability and resilience, establish engineering practices, support production operations, and mentor engineers. The role requires deep ownership of distributed data infrastructure and practical use of AI coding agents.

Designs and manages advanced analytics models and reporting tools for supply chain, inventory, fulfillment center labor, and operational performance. Builds predictive analytics to forecast key metrics, automates reporting, provides data-driven decision support, collaborates with cross-functional teams, and mentors entry-level analysts.