Cloud Engineer
Colorado , CO
|Remote
|Contract
Colorado, CO
|Remote
|Contract
Job ID 76893|Posted Nov 6, 2026
JOB DESCRIPTION
Position Summary
- We are seeking a hands-on Snowflake / Data & Application Engineer to support the development and modernization of data, reporting, analytics, and workflow capabilities within a commercial banking and credit environment.
- This role will work directly with business subject-matter experts and enterprise technology partners to translate business requirements, existing datasets, spreadsheets, reports, documents, and manual processes into working applications, analytics, automation, and reusable data products.
- The target environment uses Snowflake as a governed data foundation, with solutions potentially incorporating Streamlit, Python, SQL, Power BI, AI capabilities, and other enterprise technologies.
- Existing internal architecture also contemplates curated datasets, governed data products, semantic models, analytics, applications, and AI as different ways of consuming the same underlying data.
- This is primarily a hands-on builder role, rather than a strategy, project-management, or requirements-only position. The ideal individual can take an imperfectly defined business problem, understand the desired outcome, analyze the available data and existing process, and iteratively develop a practical solution.
Snowflake & Data Development
- Develop, test, and maintain SQL supporting applications, reporting, analytics, and business workflows.
- Build and maintain Snowflake tables, views, transformations, mappings, and application-supporting data structures.
- Work with structured, semi-structured, and unstructured data.
- Translate source-system data into reusable, business-friendly datasets.
- Perform source-to-target reconciliation, record-count validation, field-level testing, and investigation of data discrepancies.
- Assist with data modeling, relationships, historical data, and business definitions.
- Document data lineage, source mappings, transformations, dependencies, and application usage.
- Develop solutions that can appropriately progress across development, testing, and production environments.
Design, build, and enhance data-driven internal applications, particularly applications developed using Streamlit and Snowflake.
Solutions may include:
- Portfolio and management dashboards
- Data-entry interfaces
- Review and approval workflows
- Exception-management tools
- Operational workflow applications
- Administrative tools
- Tracking and assignment applications
- Data-ingestion utilities
- Data-validation interfaces
- Forecasting and analytical tools
- Document review applications
- AI-assisted workflows
Python & Automation Development
Use Python to solve business and data challenges where SQL or traditional reporting tools alone are insufficient.
Examples may include:
- Data transformation and validation
- File processing
- Excel automation
- Document parsing
- Data reconciliation
- Application business logic
- Repetitive-process automation
- Integration utilities
- Analytical calculations
- Prototype AI workflows
Application Architecture & Maintainability
Help move rapidly developed prototypes toward scalable, supportable applications.
Responsibilities may include:
- Modular application design
- Reusable Python components
- Separation of UI, business logic, and data-access logic
- Configuration-driven development
- Session and application-state management
- Query optimization and caching
- Error handling and logging
- Role/access considerations
- Environment configuration
- Source control and code documentation
- Data-to-application lineage
- Performance and concurrency troubleshooting
Reporting, Analytics & Visualization
Develop and enhance business intelligence and analytical capabilities using tools such as:
- Power BI
- Streamlit
- Snowflake
- SQL
- Python
- Excel / Power Query, where appropriate
The broader internal data strategy emphasizes trusted, governed sources for leadership reporting, automation, analytics, and AI rather than creating isolated solutions for each use case.
Workflow & Process Modernization
Assist in converting processes currently dependent on spreadsheets, email, documents, or manual activities into structured applications and workflows.
Potential capabilities include:
- Structured data collection
- Review and approval routing
- Status tracking
- Assignment and ownership management
- Exception identification
- Business-rule validation
- Controlled overrides
- Historical record retention
- Notifications and action tracking
- Audit-friendly data capture
- Administrative/configuration capabilities
Data Integration & Source-System Analysis
Work with business SMEs and technology partners to understand information originating from systems such as:
- nCino
- Salesforce
- Loan servicing platforms
- Credit and underwriting systems
- Financial-data providers
- Enterprise data repositories
- Excel-based models
- Document management platforms
- Other internal and external data sources
The contractor does not need to be the enterprise integration owner. However, this person should understand how to analyze source data, identify keys and relationships, map fields, identify data-quality concerns, and work effectively with engineering teams responsible for enterprise pipelines and system integrations.
Unstructured Data & Document Automation
Support development of capabilities that convert files and documents into structured, usable information.
Potential sources may include:
- Excel workbooks
- Financial statements
- Operational reports
- Customer-submitted documents
- PDFs
- Images
- Supporting credit documentation
- Periodic reporting packages
- Other semi-structured or unstructured files
Experience with document parsing, OCR/document intelligence, Python-based extraction, or AI-assisted document processing would therefore be valuable.
AI & Advanced Analytics
Exposure to Snowflake's AI capabilities or other enterprise AI technologies is preferred but not required.
Potential areas include:
- Snowflake Cortex
- Semantic models/views
- Natural-language analytics
- AI agents
- Document extraction
- Automated summarization
- Exception identification
- Reusable AI skills/workflows
- Human-in-the-loop AI applications
The emphasis should be on practical AI embedded within business processes, not AI experimentation for its own sake.
Required Qualifications
Snowflake / SQL
Strong working knowledge of:
- Snowflake
- Advanced SQL
- Relational data modeling
- Tables and views
- Data transformations
- Complex joins
- CTEs and window functions
- Data reconciliation and validation
- Query troubleshooting and optimization
- Development/testing/production concepts
- Access and security concepts
Strong proficiency with Python, particularly for:
- Data manipulation
- Application development
- pandas or similar libraries
- File processing
- Automation
- Business logic
- Data validation
- Excel interaction
- Reusable/modular code
Demonstrated ability to build meaningful business applications.
Experience with Streamlit is strongly preferred, including:
- Multi-page/modular applications
- Interactive forms
- Data validation
- Session/state management
- Database interaction
- Write-back functionality
- Interactive data visualization
- Application performance
- Reusable components
Strong understanding of:
- Data relationships and keys
- Data quality
- Source-to-target mapping
- Historical/trended data
- Business metrics
- Reporting logic
- Structured vs. unstructured information
- Troubleshooting inconsistent data
Experience with Power BI or a comparable enterprise BI platform strongly preferred.
Experience with Power Query, DAX, Excel, and related analytical tools is beneficial.
Preferred Experience
Banking / Financial Services
Experience in commercial banking, corporate banking, lending, credit, risk, or financial services is highly desirable.
Particularly valuable experience includes:
- Credit underwriting
- Portfolio management
- Loan monitoring
- Financial analysis
- Lending operations
- Collateral monitoring
- Covenant monitoring
- Risk management
- Structured lending/finance
Exposure to one or more of the following would be beneficial:
- nCino
- Salesforce
- Commercial loan servicing platforms
- Credit underwriting systems
- Document management systems
- Financial market/data providers
Development Tools & Technologies
Experience with some combination of the following is preferred:
- Snowflake
- Streamlit
- Python
- SQL
- Power BI
- Power Query
- DAX
- Git / version control
- VS Code
- Snowpark
- Snowflake Cortex
- REST APIs
- JSON / semi-structured data
- Excel automation
- AI/document-intelligence technologies
What Success Looks Like
- Turn business problems into working solutions
- The developer can work from a business objective rather than requiring a complete technical specification before beginning.
- Understand the data, not just the interface
- The developer traces the sources, relationships, definitions, calculations, and transformations behind what users ultimately see.
- Prototype quickly without creating technical debt
- Speed is important, but applications should remain understandable, modular, testable, and maintainable.
- Know the difference between prototype and production
- The individual understands where rapid business-led development is appropriate and where capabilities require formal engineering, security, governance, or enterprise integration support. That distinction has been an explicit consideration in the current Snowflake work.
- Diagnose problems independently
- When something doesn't reconcile or an application fails, the developer can work through the full chain:
- source data ? Snowflake ? transformation/business logic ? application/report ? user experience
- rather than troubleshooting only one layer.
- Build for reuse
- Common business requirements should become reusable datasets, components, functions, patterns, and frameworks where practical. The existing data strategy similarly emphasizes governed, reusable capabilities rather than duplicating work across use cases.
- Work effectively in ambiguity
- The individual is comfortable iterating alongside business users as requirements become clearer through working prototypes.
- Collaborate across business and technology teams
- The successful contractor can communicate comfortably with business SMEs, analysts, data engineers, architects, and technology partners and translate between those audiences.
Horizontal is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, and gender identity), national origin, age, disability, veteran status, or any other protected characteristic under applicable law.
Horizontal is committed to taking affirmative action to employ and advance in employment qualified individuals with disabilities and protected veterans. If you are an individual with a disability and require a reasonable accommodation to complete any part of the application process or participate in the interview process, click here to request accommodation assistance.
All applicants applying must be legally authorized to work in the country of employment.
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