Assistant Data & AI Architect Manager

Scope of Work

We are looking for Assistant Data & AI Architect Manager to lead enterprise-wide data, analytics, and AI transformation initiatives.

This role will define the future-state Data & AI architecture, modernize data platforms, and ensure that data and AI solutions are scalable, secure, and aligned with business goals. You will work closely with senior leaders, business teams, architects, and engineers to shape the company’s long-term Data & AI strategy.

Key Responsibilities:

• Define and lead enterprise Data & AI architecture across multiple business areas and projects.

• Design target architecture for data platforms, analytics, AI/ML, and Generative AI solutions.

• Lead modernization of legacy platforms to cloud-native or hybrid environments.

• Drive adoption of modern technologies such as lakehouse, real-time analytics, streaming, and AI platforms.

• Establish architecture standards, frameworks, and best practices across the organization.

• Guide selection and implementation of Data, Analytics, AI/ML, and GenAI technologies.

• Define approaches for MLOps, AI governance, model lifecycle management, and AI monitoring.

• Ensure data quality, governance, privacy, security, and regulatory compliance.

• Translate business needs and AI opportunities into practical technology roadmaps.

• Advise senior management on architecture decisions, technology investments, risks, and priorities.

• Review solution designs and provide technical guidance to architects, engineers, and AI teams.

• Coach and mentor Data & AI professionals and promote architecture best practices across the organization.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Artificial Intelligence, or a related field.

• 5-7 years of experience in Data, Analytics, AI, or Architecture roles.

• Strong experience designing enterprise or large-scale Data & AI architectures.

• Strong knowledge of cloud data platforms, lakehouse, streaming, and real-time analytics.

• Experience with AI/ML platforms, MLOps, AI governance, and model lifecycle management.

• Knowledge or hands-on exposure to Generative AI and Large Language Models (LLMs).

• Experience working in complex, data-intensive, or regulated environments is preferred.

• Strong business understanding with the ability to translate business requirements into technology solutions.

• Excellent communication and stakeholder management skills, especially with senior management.

• Strong leadership, mentoring, analytical, and problem-solving skills.

• Certifications such as Azure Data/AI, AWS Data Analytics, TOGAF, or SAFe Architect are an advantage.