VP of Data

At Suffolk Credit Union, we empower our members and strengthen our community by promoting financial wellness, transparency, and respect. Join us to enjoy comprehensive benefits, including health plans, 401(k) matching, and support for work-life balance, along with employee engagement activities and opportunities for community involvement.

Role Overview: As the VP, Data & Analytics, you will play a pivotal role in designing and implementing best-in-class data management solutions for metadata, master data, and data quality management. This role serves as both a hands-on enterprise data architect and a people leader, responsible for guiding technical direction while mentoring data engineering and analytics staff. Your work will enable advanced data analytics capabilities across the organization, to support our member-centric mission.

Key Responsibilities:

• Develop and execute the high-level data strategy, system design, and overall architecture of the Credit Union's data ecosystem.
• Own and continuously improve enterprise data quality by defining, implementing, and monitoring standardized data quality metrics across the organization. Establish governance and controls to ensure accuracy, completeness, consistency, and timeliness.
• Design, develop, test, and implement robust solutions for metadata, master data, and data quality management using technologies such as SQL, C#, Power BI, Azure Data Factory, Logic Apps, Event Hub, and related platforms.
• Build and support data engineering frameworks, ETL/ELT processes, and warehouse models, while creating reporting and analytical applications that transform complex data into actionable insights for stakeholders. Lead data architecture review sessions for acquisition and integration projects, providing actionable recommendations to stakeholders and technical teams.
• Perform complex data analysis across multiple platforms using SQL, Excel, Power BI, and other tools to deliver insights and inform business decisions.
• Oversee the Data Governance program, ensuring the optimization of data infrastructure and implementation of best practices for compliance and security.
• Partner with stakeholders cross-functionally to ensure alignment between data architecture and business objectives.
• Manage and mentor a team of Data Engineers and Analysts, fostering a high-performance, collaborative work environment.
• Oversee key vendor relationships for data platforms and tools, conduct RFP processes as needed, and serve as the business owner for any system implementations, upgrades, or decommissions.
• Ensure compliance with all applicable laws, regulations, policies, and risk management requirements.
• Drive continuous improvement of data architecture and analytics capabilities.
• Perform additional duties as requested by leadership.

Essential Qualifications:

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  Advanced expertise in SQL and Python, with strong experience in ELT frameworks and tools (DBT preferred).

  
  
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  Deep knowledge of cloud architecture, ETL/ELT pipelines, data transfers, and orchestration using Airflow.

  
  
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  Proven leadership in data warehouse implementations and automated ETL/ELT development across multiple source systems.

  
  
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  Minimum 7+ years of experience in data architecture, including 5+ years within Financial Services or a comparable regulated industry.

  
  
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  Demonstrated experience implementing enterprise data architecture models, data governance frameworks, system integrations, and delivering metadata management, master data management, and data quality solutions in complex environments.

  
  
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  Hands-on experience with Snowflake, SQL Server, and SQL Server Master Data Services.

  
  
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  Proficiency in data analysis and visualization tools, including Power BI, Python, and R; experience with version control systems, CI/CD pipelines, and Agile/SCRUM methodologies.

  
  
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  Strong communication, project management, and change management skills, with the ability to translate complex technical concepts for non-technical stakeholders and drive cross-functional adoption.

  
  
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  Bachelor's degree in Computer Science, Data Science, Information Systems, or a related field (required); Master's degree in Data Science, Information Systems, or Business Administration with a technical focus (preferred).