Etl Developer Remote Jobs in Miami, FL (NOW HIRING)

software engineering, data engineering, AI/ML, or solution consulting roles,
Experience working directly with business stakeholders and translating requirements into technical solutions.
Python, SQL, APIs and Microservices, Cloud Platforms (Azure preferred, AWS or GCP acceptable), Machine Learning and Data Science fundamentals
•           8+ years of experience in software engineering, data engineering, AI/ML, or solution consulting roles.
•           Experience working directly with business stakeholders and translating requirements into technical solutions.
•           Demonstrated experience delivering AI-enabled business transformation initiatives.
Technical Skills
•           Python
•           SQL
•           APIs and Microservices
•           Cloud Platforms (Azure preferred, AWS or GCP acceptable)
•           Machine Learning and Data Science fundamentals
•           Generative AI and Large Language Models
•           Retrieval-Augmented Generation (RAG)
•           Vector Databases
•           LangChain, LlamaIndex, Semantic Kernel, or similar frameworks
•           Git, CI/CD, DevOps practices
Data & Analytics
•           Data Engineering
•           Data Modeling
•           Power BI/Tableau
•           Data Visualization
•           ETL/ELT processes
________________________________________
Preferred Qualifications
Commercial Real Estate Domain Knowledge
Experience in one or more of the following:
•           Commercial Real Estate (CRE)
•           Mortgage Loan Servicing
•           CMBS
•           Asset Management
•           Special Servicing
•           Real Estate Investment Management
•           Distressed Assets Management
•           Portfolio Risk Management
Consulting & Client-Facing Skills
•           Strong executive communication skills.
•           Ability to present AI concepts to both technical and non-technical audiences.
•           Experience working in consulting or customer-facing environments.
•           Ability to manage ambiguity and solve complex business problems.
Roles & Responsibilities
 Key Responsibilities
Business & Domain Engagement
•           Partner closely with Rialto business leaders and operational teams to understand workflows, pain points, and strategic objectives.
•           Translate complex business requirements into scalable AI, automation, and analytics solutions.
•           Act as a trusted advisor for AI adoption across Commercial Real Estate and Loan Servicing operations.
•           Conduct discovery workshops and identify high-value use cases for AI and GenAI implementation.
AI Solution Development & Deployment
•           Design, build, and deploy AI-powered applications leveraging GenAI, LLMs, Agentic AI, and machine learning technologies.
•           Develop proof-of-concepts (POCs) and rapidly iterate into production-grade solutions.
•           Build AI assistants and copilots to support:
o          Asset Management
o          Loan Servicing
o          Special Servicing
o          Investor Reporting
o          Document Processing
o          Portfolio Risk Monitoring
•           Integrate AI solutions with enterprise platforms and existing business applications.
Data Engineering & Analytics
•           Work with structured and unstructured data from:
o          Mortgage Loans
o          CMBS Portfolios
o          Property Financials
o          Servicing Platforms
o          Investor Reports
o          Legal and Asset Documents
•           Design data pipelines and AI-ready datasets.
•           Create dashboards and actionable business insights using modern analytics tools.
Product & Technology Delivery
•           Collaborate with engineering and architecture teams to deploy scalable solutions.
•           Drive end-to-end implementation from ideation through production deployment.
•           Monitor adoption, business value realization, and continuous optimization.
•           Ensure compliance with data governance and security standards.
Innovation & Thought Leadership
•           Stay current on emerging AI technologies, frameworks, and industry trends.
•           Recommend innovative ways to improve efficiency, reduce operational costs, and enhance decision-making.
•           Champion AI-first thinking across business processes.