Data & AnalyticsData Engineering, Business Intelligence
About the job
Requirements
Strong software engineering experience using modern programming languages and cloud-native development practices.
Advanced proficiency in SQL, Python, application programming interfaces (APIs), Git-based development, and modern software engineering methodologies.
Experience with enterprise cloud platforms including Snowflake, Microsoft Fabric, Azure, Databricks, or similar technologies.
Experience designing enterprise architectures, reusable business capabilities, and modern data ecosystems.
Strong understanding of enterprise governance, security, metadata, and integration architecture.
A bachelor's degree in Computer Science, Software Engineering, Data Science, Information Systems, Engineering, or equivalent professional experience.
Five or more years designing and delivering enterprise software, analytics, artificial intelligence, or cloud data solutions.
Responsibilities
Design, architect, develop, and implement end-to-end enterprise intelligence solutions to solve complex business challenges.
Transform business capabilities into reusable enterprise intelligence products that support 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 to optimize scalability, reliability, governance, security, maintainability, and cost efficiency.
Lead technical solution design across multiple technologies while promoting engineering excellence and innovation.
Design and develop cloud-native data platforms, integration frameworks, application programming interfaces, and enterprise data pipelines.
Engineer reusable enterprise data products, semantic models, and curated datasets that support analytics and artificial intelligence.
Optimize enterprise data processing, storage, and cloud platform performance.
Implement DataOps, continuous integration and continuous delivery (CI/CD), Infrastructure as Code, automated testing, observability, and operational monitoring.
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.
Design and develop artificial-intelligence-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.
Develop enterprise applications, application programming interfaces, 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.
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.
Perform other related duties as assigned.
Desired Qualifications
Experience with Generative AI, AI agents, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG).
Experience developing enterprise applications using Streamlit, React, .NET, or similar technologies.
Experience with DevSecOps, CI/CD, Infrastructure as Code, DataOps, and MLOps.
Experience within mortgage loan originations, mortgage servicing, or the broader financial services industry.
Professional certifications related to Azure, Snowflake, Microsoft Fabric, AWS, Google Cloud, AI, or software engineering.
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.
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:
This position is an individual contributor.
Qualifications:
To perform this job successfully, an individual must be able to perform each essential function satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required.
Strong software engineering experience using modern programming languages and cloud-native development practices.
Advanced proficiency in SQL, Python, APIs, Git-based development, and modern software engineering methodologies.
Experience with enterprise cloud platforms including Snowflake, Microsoft Fabric, Azure, Databricks, or similar technologies.
Experience designing enterprise architectures, reusable business capabilities, and modern data ecosystems.
Strong understanding of enterprise governance, security, metadata, and integration architecture.
Excellent analytical thinking, communication, collaboration, and stakeholder engagement skills.
Preferred Qualifications
Experience with Generative AI, AI agents, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG).
Experience developing enterprise applications using Streamlit, React, .NET, or similar technologies.
Experience with DevSecOps, CI/CD, Infrastructure as Code, DataOps, and MLOps.
Experience within mortgage loan originations, mortgage servicing, or the broader financial services industry.
Professional certifications related to Azure, Snowflake, Microsoft Fabric, AWS, Google Cloud, AI, or software engineering.
Education and/or Experience:
Bachelor's degree in Computer Science, Software Engineering, Data Science, Information Systems, Engineering, or equivalent professional experience.
Five or more years designing and delivering enterprise software, analytics, AI, or cloud data solutions.
Certificates, Licenses, Registrations:
None Required
Work Complexity:
Problems and issues faced are difficult and complex, and may require understanding of broader set of issues. Problems typically involve consideration of multiple issues and understanding of the financial/mortgage industry. Problems are typically solved through drawing from prior experience and analysis of issues.
Work Environment:
The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Work is normally performed in a typical interior office work environment which does not subject the employee to any hazardous or unpleasant elements. The noise level in the work environment is usually moderate.
Physical Demands:
The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. While performing the duties of this job, the employee is frequently required to sit and talk or hear. The employee is occasionally required to stand; walk; use hands to finger, handle, or feel; and reach with hands and arms. The employee must occasionally lift and/or move up to 25 pounds.
Equal Employment Opportunity:
The company is committed to providing equal employment opportunities to all employees and applicants without regard to race, ethnicity, color, sex, marital status, sexual orientation, gender identity or expression, pregnancy, religion, national origin, age (40 and over), disability, military status, genetic information, or any other basis protected by applicable federal, state, or local laws.
Americans with Disabilities Act:
Applicants as well as employees who are or become disabled must be able to satisfactorily perform the essential job functions of the position either with or without reasonable accommodation. Applicants as well as employees are encouraged to meet with Human Resources as the organization shall review reasonable accommodations on a case-by-case basis in accordance with applicable law.
Job Responsibilities:
The statements reflect the general duties and responsibilities considered necessary to perform the essential functions of the job and should not be considered as an all-inclusive list of all the work requirements of the position. The company may change the specific job duties with or without prior notice based on the needs of the organization.