VP, Director of Data Engineering - Information Technology

SUMMARY:

The VP, Director of Data Engineering is a strategic and hands-on leadership role responsible for defining and executing the vision for enterprise data engineering, pipeline development, and platform architecture. This position leads the design, development, and operational oversight of scalable data pipelines and systems that enable data integration, analytics, reporting, and data science across the organization.

 

This leader ensures the delivery of secure, compliant, and high-performing data environments by guiding engineering and architecture teams through the design and operation of robust, modern data platforms. The role is critical in advancing the Bank’s data maturity and driving business value through efficient data practices and infrastructure.

 

OTHER QUALIFICATIONS:

Extensive experience in designing and managing complex data pipelines, platform architecture, and distributed data systems required.

Strong programming and scripting skills in SQL, Python, R, and experience with ETL/ELT tools and orchestration frameworks required.

Hands-on experience with modern data platforms such as Snowflake, Databricks, Amazon Redshift, BigQuery, or similar required.

Proven success in leading and scaling cross-functional technical teams in data engineering and platform architecture required.

Proficiency in cloud-based data platforms (e.g., AWS, Azure, Google Cloud) and hybrid cloud/on-premises architectures.

Familiarity with enterprise architecture frameworks (e.g., TOGAF), CI/CD pipelines, version control, and DevOps tools.

Knowledge of metadata management, data quality frameworks, and data lineage tooling.

Demonstrated ability to align data initiatives with business strategies and drive measurable impact.

Strong interpersonal and communication skills with the ability to influence stakeholders at all levels.         

Ability to communicate effectively with technical and non-technical stakeholders.

 

SUPERVISORY RESPONSIBILITIES:                                                   

Carries out supervisory responsibilities in accordance with the organization’s policies and applicable laws. 

Responsibilities include interviewing, hiring, and training employees; planning, assigning, and directing work; appraising performance; rewarding and disciplining employees; addressing complaints and resolving problems.

 

CUSTOMER SERVICE SKILLS:

Willingness to provide a level of service which will clearly differentiate us from our competitors.

 

INTERPERSONAL SKILLS:

Professional demeanor in appearance, interpersonal relations, work ethic and attitude.

Possess clear, concise, effective written and oral communication skills to effectively express thoughts, ideas and concepts to management, bank employees and bank customers in a collaborative and solutions oriented manner.

 

ESSENTIAL DUTIES AND RESPONSIBILITIES:

Strategic Leadership

Defines and leads the strategic vision for enterprise data pipelines and platform architecture to align with business priorities and regulatory obligations.

Guides modernization of legacy systems by adopting new technologies and cloud-based infrastructure to support advanced analytics, reporting, and real-time decision-making.

Influences the enterprise data strategy through collaboration with executive leadership and other technology functions.

 

Data Engineering & Pipeline Development

Owns the full data lifecycle, including data ingestion, transformation, integration, storage, and consumption across analytical and operational platforms.

Designs and implements scalable ETL/ELT pipelines and real-time streaming data workflows to enable business intelligence, regulatory reporting, and data science use cases.

Ensures pipeline efficiency, resiliency, and data quality through best-in-class engineering practices and observability.

 

Architecture & Platform Oversight

Oversees the design and optimization of hybrid (cloud and on-prem) data architectures that are scalable, secure, and cost-effective.

Defines and enforces enterprise data modeling standards, metadata practices, and architectural frameworks to ensure consistency and reuse across solutions.

Leads evaluation and integration of modern data platforms and tools to accelerate development and performance.

 

Operations, Monitoring & Compliance

Establishes operational monitoring, observability, and incident response capabilities for data platforms and pipelines.

Ensures compliance with data governance policies, data privacy laws, security frameworks, and industry-specific regulations (e.g., GLBA, FFIEC).

Partners with Information Technology (IT), Risk, Compliance, and Security teams to embed controls, protect data assets, and ensure audit readiness.

 

Collaboration & Influence

Collaborates with business stakeholders, analytics teams, and IT to gather requirements and translate them into scalable data solutions.

Promotes enterprise-wide data literacy and platform adoption by aligning engineering efforts with business value.

Advocates for data best practices and architectural discipline across the organization.

 

Team Leadership

Builds, manages, and mentors high-performing teams in data engineering, architecture, and platform operations.

Manages offshore personnel ensuring alignment, productivity, and integration with existing teams

Promotes a culture of innovation, technical excellence, accountability, and continuous improvement.

Provides coaching and career development opportunities to advance team capabilities.

 

OTHER REQUIREMENTS:

Banking is a highly regulated industry and you will be expected to acquire and maintain a proficiency in the Bank's policies and procedures, and adhere to all laws, rules and regulations that are applicable to your conduct and the work you will be performing.  You will also be expected to complete all assigned compliance training in a timely manner.

Qualifications

Bachelor’s degree in Computer Science, Data Science, Information Systems, Engineering, or a related field required; Master’s degree preferred.

Minimum of ten years of progressive experience in data engineering and architecture roles required, including a minimum of five years in a leadership capacity.

Experience in the financial services industry or other highly regulated environments preferred.