Solutions Architect - Data Engineering

FourLeaf Federal Credit Union is seeking a Solutions Architect – Data Engineering to lead the design, development, and scaling of its enterprise data platform. The role combines strategic architecture with hands-on engineering across data ingestion, integration, governance, observability, cost optimization, semantic modeling, analytics, and machine learning enablement.

Responsibilities:

• Design and maintain an enterprise data platform that provides a unified, governed view of credit union operations across all domains
• Implement Bronze/Silver/Gold layer strategy with data contracts, transformation standards, and quality expectations
• Create and maintain enterprise data models for Member, Deposit, Transaction, Lending, Finance, Marketing, Digital, and Regulatory domains
• Define architectural patterns, modeling standards, naming conventions, and documentation practices
• Develop and maintain reference architectures and reusable design patterns for the broader EDAO team
• Lead the design of ingestion pipelines for 75+ systems of record including digital platforms, payment processors, lending systems, and third‑party providers
• Build reusable ETL/ELT patterns, templates, and parameterized components
• Standardize batch, near‑real‑time, and streaming ingestion methods
• Implement error handling, retry logic, and alerting frameworks
• Define approaches for database connections, APIs, file transfers, and CDC‑based ingestion
• Embed validation, profiling, and quality checks within ingestion workflows
• Lead mid‑to‑large data initiatives from requirements through deployment
• Translate complex business needs into technical specifications, data models, and implementation plans
• Build critical pipelines, transformations, and data products while setting engineering quality standards
• Serve as the expert problem solver for performance challenges, integration issues, and architectural decisions
• Work directly with business analysts, product owners, and subject matter experts to understand requirements and deliver solutions that meet business needs
• Design frameworks for monitoring data quality, freshness, pipeline reliability, and lineage
• Implement proactive alerts and incident‑response processes
• Define, measure, and optimize SLAs for critical business processes
• Introduce automated testing, CI/CD pipelines, and environment management
• Develop runbooks and lead root‑cause analysis for operational issues
• Implement Snowflake cost‑management strategies including monitoring, warehouse optimization, and chargeback/showback models
• Optimize queries, warehouse sizing, and resource utilization to balance performance and cost
• Analyze consumption trends and identify optimization opportunities
• Partner with finance and IT to forecast and manage Snowflake spend
• Define and enforce development practices supporting cost‑efficient usage
• Use AI tools to accelerate pipeline development, code generation, and documentation
• Leverage Cortex capabilities for data processing and enrichment
• Identify repetitive engineering tasks suitable for AI‑driven automation
• Stay current on AI advancements relevant to data engineering and evaluate adoption opportunities
• Build and maintain a semantic layer with consistent business definitions, metrics, and data products
• Develop comprehensive member‑centric data products that enable insights into behavior, engagement, and opportunities
• Deliver enterprise KPIs for Lending, Deposits, Digital, Branch Performance, and more
• Support NCUA, BSA/AML, GLBA, and other compliance requirements through curated data products
• Optimize models for consumption in Power BI and Sigma Computing
• Build the data infrastructure and feature stores required for predictive modeling (risk, churn, behavior, growth)
• Enable next‑best‑action and prescriptive decision‑support pipelines
• Work with data scientists to operationalize models and ensure reliable data flows and monitoring
• Maintain secure, well‑structured environments for experimentation and advanced analytics

Requirements:

• Bachelors Degree in Computer Science, Information Technology, or related field
• 15+ years of progressive experience in data engineering, data architecture, database development, and enterprise analytics with experience in solution architecture and technical leadership roles with demonstrated ownership of enterprise-scale data platforms
• Snowflake required
• Hands-on experience with cloud data platforms
• Experience with modern ETL/ELT tools
• SQL
• Python
• ETL tools
• Data Visualization tools (Power BI, Sigma, and or Tableau)
• cloud platforms (AWS, Azure, or Google Cloud)
• Microsoft Office (Excel, Word, PowerPoint, Teams, Outlook)
• This position requires at least one of the certifications listed below
• SnowPro Advanced: Architect and SnowPro Advanced: Data Engineer
• Matillion Associate or Professional Certification
• Databricks Certified Data Engineer Professional or Databricks Certified Machine Learning Professional
• AWS Certified Data Analytics or Solutions Architect
• Masters degree in Computer Science, Information Technology, or related field
• additional cloud DW experience valued
• Matillion expertise strongly preferred
• Additional certifications are considered a plus