Enterprise Intelligence Solutions Engineer

Summary:

The Enterprise Intelligence Solutions Engineer designs, architects, develops, and supports modern enterprise intelligence products, cloud data platforms, analytics solutions, and AI-enabled applications that empower business decision-making. This role combines software engineering, cloud data engineering, analytics engineering, solution architecture, data science, artificial intelligence, and deep expertise in mortgage loan origination and mortgage servicing to deliver scalable, governed, secure, and high-performing enterprise capabilities.

Working collaboratively with fellow Enterprise Intelligence Solutions Engineers and business stakeholders, this role serves as a multidisciplinary engineering professional responsible for solution architecture, software engineering, data engineering, analytics engineering, data science, and AI solution development. The Enterprise Intelligence Solutions Engineer transforms business opportunities into intelligent, scalable, and reusable enterprise solutions that improve operational efficiency, customer experience, regulatory compliance, and business performance.

This role owns the complete solution lifecycle—from business discovery and process analysis through solution architecture, engineering, deployment, operational support, and continuous optimization—while ensuring alignment with enterprise architecture, governance, security, and engineering standards.

Essential Job Duties and Responsibilities:

• Enterprise Intelligence Engineering
• Design, architect, develop, and implement end-to-end enterprise intelligence solutions that solve complex business challenges.
• Transform business capabilities into reusable enterprise intelligence products supporting analytics, automation, artificial intelligence, and operational excellence.
• Collaborate with fellow Enterprise Intelligence Solutions Engineers to establish engineering standards, architectural patterns, and reusable solution frameworks.
• Apply enterprise architecture principles that optimize scalability, reliability, governance, security, maintainability, and cost efficiency.
• Lead technical solution design across multiple technologies while promoting engineering excellence and innovation.
• Cloud Data & Platform Engineering
• Design and develop cloud-native data platforms, integration frameworks, APIs, and enterprise data pipelines.
• Engineer reusable enterprise data products, semantic models, and curated datasets supporting analytics and artificial intelligence.
• Optimize enterprise data processing, storage, and cloud platform performance.
• Implement DataOps, CI/CD, Infrastructure as Code, automated testing, observability, and operational monitoring.
• Analytics, Data Science & Decision Intelligence
• Develop analytical models, forecasting solutions, executive dashboards, KPIs, and decision-support capabilities.
• Perform exploratory data analysis, statistical modeling, and predictive analytics.
• Apply machine learning techniques, where appropriate, to improve operational performance and customer outcomes.
• Develop governed semantic models that simplify access to trusted enterprise information.
• Artificial Intelligence Engineering
• Design and develop AI-enabled enterprise applications and intelligent automation solutions.
• Build AI agents, Retrieval-Augmented Generation (RAG) solutions, enterprise copilots, and natural language interfaces.
• Integrate Large Language Models (LLMs) into enterprise applications using responsible AI principles.
• Evaluate emerging AI technologies and recommend innovative business solutions.
• Software & Application Engineering
• Develop enterprise applications, APIs, and modern user experiences that improve access to enterprise intelligence.
• Apply modern software engineering practices, including version control, peer reviews, automated testing, DevSecOps, and continuous integration.
• Engineer highly maintainable, secure, and scalable software solutions.
• Enterprise Governance & Engineering Excellence
• Embed governance, metadata, lineage, security, privacy, and data quality into every solution.
• Ensure compliance with enterprise architecture, regulatory requirements, and organizational standards.
• Develop reusable engineering standards, templates, accelerators, and best practices.
• Mentor fellow engineers while fostering innovation and continuous improvement.
• Comply with all company policies and procedures.
• Maintain regular and punctual attendance.

Other Job Duties and Responsibilities:

Performs other related duties as assigned.

Supervisory Responsibilities