Director, Principal Data Architect

Director, Principal Data Architect

Department: Data

Employment Type: Full Time

Location: Remote

Description

Grasshopper Bank is a client-first, digital bank built for the business and innovation economy, with an obsession for providing leading-edge technology, solutions-driven products and superior service through a combination of passionate people and digital resources.
We are a highly experienced team who pride ourselves on diversity of thought and perspective.  Nationally chartered, our portfolio of products and services range from VC, PE & Portfolio Companies to SBA Lending, as well as direct SMB and Embedded Banking.
Our entrepreneurial drive allows us to support the growth and success of a wide range of clients at every stage of their business through inclusive partnership.  We seek out team members who will enable both our organization and our people to grow and thrive through collaboration and acting with integrity and respect.
Our focus on cross-functional teamwork provides a culture where ideas are valued, accountability is encouraged, and successes are celebrated. We welcome all those searching for the opportunity to contribute to banking innovation that influences and supports the emerging digital world of Financial Services.
Our digital first approach enables our teams the flexibility to work remotely. We have offices in NYC and Boston.

What you'll do:

Reporting to our Chief Data Officer, you will lead the design, development, and implementation of our enterprise data architecture. This role is critical in driving our data strategy, ensuring data quality, and enabling data-driven insights across the organization. The Principal Data Architect will be responsible for defining the overall data architecture roadmap, establishing best practices, and mentoring other data professionals.
Responsibilities include:

Strategic Data Architecture Leadership:

• Develop and maintain the enterprise data architecture strategy and roadmap, aligning with business objectives and technological advancements.
• Provide thought leadership and guidance on data architecture principles, standards, and best practices.
• Evaluate and recommend emerging data technologies and tools to enhance data capabilities.
• Collaborate with senior leadership to define data governance policies and procedures.

Data Design:

• Design and implement scalable and efficient data infrastructure.
• Establish data standards and ensure consistency across all data assets.
• Optimize data storage, retrieval, and processing for performance and efficiency.
• Design solutions for data integration, data warehousing, and data lakes.

Data Governance and Quality:

• Establish and enforce data governance policies and standards to ensure data quality, security, and compliance.
• Define and implement data quality metrics and monitoring processes.
• Develop and maintain data dictionaries and metadata repositories.
• Ensure compliance with relevant data privacy regulations (e.g., CCPA).

Technology Evaluation and Implementation:

• Evaluate and select appropriate data technologies and tools.
• Design and implement data integration solutions using various technologies and methods.
• Architect and implement cloud-based data solutions (e.g., GCP).

Collaboration and Mentorship:

• Collaborate with cross-functional teams, including data engineers, data scientists, and business analysts, to deliver data solutions.
• Mentor and guide junior data architects and engineers, fostering a culture of continuous learning and development.
• Communicate complex technical concepts to non-technical stakeholders.
• Work with security teams to ensure data security best practices.

What you need:

• Bachelor's or Master's degree in Computer Science, Information Systems, or a related field.
• Minimum of 10+ years of experience in data architecture, and data management.  
• Proven experience in designing and implementing enterprise-level data architectures. 
• Extensive experience with relational and non-relational databases, data warehouses, and data lakes.
• Strong understanding of data integration, and data governance principles.
• Experience with cloud-based data platforms (e.g., GCP).
• Experience in AI/ML