Senior Director -Enterprise Architecture and AI

Responsibilities

• Lead, manage, and mentor teams of architects and data engineers at varying levels, API developers and managers, fostering a collaborative and high-performance work environment to meet business objectives.
• Develop and execute a comprehensive data strategy that aligns with the organization’s goals, focusing on cloud-based data solutions and platforms like Snowflake.
• Enterprise Architecture: Design and implement scalable enterprise and business application architectures, ensuring integration with existing systems and alignment with business objectives.
• Cloud and SaaS Solutions: Lead the adoption and optimization of cloud-based and SaaS solutions, ensuring they meet security, scalability, and performance standards.
• Data Infrastructure: Architect and manage robust data infrastructures, including data lakes, to support advanced analytics, business intelligence, and operational needs.
• API Management: Oversee the design, implementation, and maintenance of restful APIs, ensuring they enable seamless integration and communication between systems and applications.
• Data Governance: Establish and enforce data governance policies and best practices to ensure data quality, security, and compliance with regulatory requirements.
• Innovation and Continuous Improvement: Drive continuous improvement and innovation in data engineering and enterprise architecture practices, staying current with industry trends and emerging technologies.
• Resource Allocation and Budget Management: Manage resources effectively, including budget planning and allocation, to support data and application architecture initiatives and ensure optimal use of technology investments.

Qualifications

• Minimum of 8 years of technology experience, focused on enterprise architecture, API management and data engineering, with increasing levels of responsibility and a minimum of 5 years in a senior leadership position managing teams and managers.
• Minimum 3 years of direct people management experience (including those who manage others) with a track record of consistently recognizing and rewarding excellent performance and effectively managing team and individual performance issues head-on, without delay.
• Experience with cloud-based data solutions, particularly with platforms such as Snowflake, Jitterbit, AWS, Azure, or Google Cloud.
• Demonstrated experience in designing and implementing complex enterprise and business application architectures.
• In-depth knowledge and experience with SaaS solutions, including their deployment, management, and optimization.
• Significant experience architecting and managing data infrastructures, including data lakes and data warehouses.
• Hands-on experience with API design, implementation, and management to ensure seamless system integration.
• Proven ability to work effectively with cross-functional teams, stakeholders, and leaders to drive alignment and project success.
• Actively remaining current with the latest industry trends, emerging technologies, and best practices in data engineering and enterprise architecture. Experience deploying AI-enabled solutions in production and guiding practical AI adoption across business or engineering workflows.