DATA ARCHITECT

POSITION PURPOSE

The Data Architect is a critical founding role responsible for transforming Mocse's data from a fragmented resource into a strategic asset. This role will establish automated reporting capabilities, build data governance foundations, develop advanced analytics, and drive continuous experimentation and optimization. This is a high-impact, high-visibility position reporting to the Vice President of Performance and Risk and working closely with executive leadership to make Mocse a truly data-driven organization.

ESSENTIAL JOB FUNCTIONS

Data Access & Reporting

• Automated Reporting & Analytics
• Design, develop, and automate reports that deliver critical information to operational groups and provide analytics and KPIs for leadership
• Reduce report turnaround times and enable self-service access to data
• Create and maintain dashboards for executives, department heads, and business users
• Establish refresh schedules and monitoring procedures for all reporting
• Migrate and optimize reports as systems and platforms evolve
• Data Integration & Management
• Integrate disparate data sources across multiple database platforms (core banking, lending platform, digital platform, card systems)
• Create direct connections to source systems and build automated data pipelines
• Design standardized data models for member, account, and transaction entities
• Determine appropriate software tools based on assignment goals
• Document all transformations, data lineage, and business rules

Data Governance & Quality

• Data Documentation & Governance
• Catalog and document data sources, definitions, and business rules across all systems
• Assess and monitor data quality; identify and resolve data issues
• Support the Data Governance Council and implement governance policies
• Develop and maintain data classification schema and access control principles
• Ensure compliance with NCUA, FFIEC, CCPA, GLBA, and Right to Financial Privacy Act requirements
• Draft and maintain documentation of procedures for generating reports and accessing data

Advanced Analytics & Insights

• Strategic Analysis & Predictive Analytics
• Research and analyze data trends to identify areas of opportunity and inform strategic decision-making
• Develop predictive models for member churn, loan default risk, fraud detection, and lifetime value
• Create member segmentation and personalization analytics for targeted marketing
• Build operational intelligence including anomaly detection, process optimization, and forecasting
• Perform demographic and geographic analysis to contribute to operations and marketing planning
• Risk Management & Fraud Analytics
• Develop real-time fraud monitoring dashboards and transaction anomaly detection
• Create member risk segmentation and geographic risk analysis
• Support compliance reporting and audit requirements
• Monitor data security and privacy controls
• Member Experience Analytics
• Build 360-degree member views combining all product relationships
• Develop member journey analytics across channels
• Create churn prediction and early warning indicators
• Analyze product affinity and identify cross-sell opportunities
• Track member satisfaction, NPS, and experience metrics
• Operational Efficiency Analytics
• Measure process cycle times (loan approval, account opening, etc.)
• Analyze channel utilization and cost per transaction
• Track employee productivity metrics and branch performance
• Monitor system performance and data quality dashboards

Stakeholder Collaboration & Communication

• Business Partnership & Requirements Gathering
• Work directly with stakeholders to identify analytical needs
• Translate business problems into data solutions
• Regularly update stakeholders on progress and recommend improvements
• Synthesize, visualize, and communicate complex information to diverse audiences
• Assist teams with targeting and campaign analytics

Continuous Improvement & Innovation

• Platform Optimization & Experimentation
• Continuously optimize analytics platform performance and cost efficiency
• Experiment with new analytical techniques, tools, and methodologies
• Expand data integration and real-time capabilities as business needs evolve
• Develop APIs for data access by applications
• Stay current on BI tools, analytics best practices, and industry trends

Professional Development & Collaboration

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• Enhance job performance by applying up-to-date professional and technical knowledge gained through training, publications, and professional relationships
• Participate in committee, community, and group projects as assigned
• Mentor others and build data literacy across the organization
• Contribute to attaining Credit Union objectives by accomplishing related results as assigned.

Qualifications

KNOWLEDGE, SKILLS, AND ABILITIES REQUIRED:

Technical Expertise (Must-Have)

• Advanced SQL proficiency - Ability to write complex queries, optimize performance, and work across multiple database platforms
• BI tool expertise - Hands-on experience with modern BI platforms (Power BI, Tableau, Looker, or similar)
• Data integration skills - Proven ability to connect disparate data sources and build automated data pipelines
• Advanced Excel proficiency - Pivot tables, advanced formulas, macros, Power Query
• Data visualization mastery - Ability to create compelling, intuitive dashboards and reports for diverse audiences
• Relational database understanding - Strong grasp of database design, normalization, and data modeling principles
• Artificial intelligence – Ability to utilize AI comfortably to assist with Mocse’s strategic initiatives

Preferred Technical Skills

• Experience with Python, R, or SAS for statistical analysis and predictive modeling
• Familiarity with cloud-based analytics platforms (AWS, Azure, Snowflake, or similar)
• Knowledge of ETL/ELT processes and tools
• Understanding of data governance frameworks and master data management
• Experience with machine learning and predictive analytics

Business & Industry Knowledge

• Financial services background strongly preferred - Credit union or banking experience is highly desirable
• Understanding of core banking systems, lending platforms, and card processing systems
• Familiarity with fraud detection, risk management, and regulatory compliance requirements
• Knowledge of member lifecycle analytics and retention strategies

Core Competencies

• Self-starter mentality - Ability to work independently with minimal supervision and take ownership of deliverables
• Excellent communication skills - Written, oral, and presentation abilities to communicate complex data insights to non-technical stakeholders
• Analytical and problem-solving skills - Ability to identify root causes, spot trends, and recommend actionable solutions
• Project management capability - Strong organizational skills, ability to prioritize competing demands, and deliver results
• Attention to detail - Work accurately with close attention to data quality and report accuracy
• Adaptability and experimentation mindset - Comfortable with ambiguity, excited by experimentation, and able to pivot quickly based on business needs
• Collaboration - Ability to build relationships across departments and influence without authority
• Ethical conduct - Demonstrates highest level of integrity when handling confidential member and business data
• Initiative and continuous improvement orientation - Takes proactive action, anticipates needs, and continuously seeks optimization opportunities
• Ability to maintain confidentiality of sensitive member and business information
• Professional demeanor - Exhibits a professional, businesslike appearance and approach

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QUALIFICATIONS:

Required

• Bachelor's degree in a quantitative field - Business Information Systems, Computer Science, Data Analytics, Statistics, Finance, Mathematics, Engineering, or related field
• Minimum 3-5 years of hands-on experience in business intelligence, data analytics, or reporting roles
• Proven track record of delivering automated reporting solutions and building analytics capabilities
• Demonstrated experience working with multiple data sources and integrating disparate systems
• Must be bondable

Strongly Preferred

• Financial services experience - Credit union or banking background
• Data governance experience - Participation in data quality, documentation, or governance initiatives
• Cloud analytics platform experience - Modern BI and cloud data warehouse implementations
• Predictive analytics experience - Building and deploying machine learning models
• Professional certifications - Microsoft Certified Data Analyst, Tableau Desktop Specialist, or similar