- Define and implement enterprise data platform architecture aligned with business objectives and technology standards.

- Design scalable and robust data solutions using Snowflake and modern cloud data technologies.

- Provide technical leadership and architectural guidance to data engineering teams.

- Drive the design and implementation of ELT/ETL pipelines, data models, and transformation frameworks using dbt.

- Develop data platform strategies, technical roadmaps, and solution designs.

- Review and guide technical implementations, ensuring adherence to architecture standards and best practices.

- Optimize Snowflake architecture, performance, scalability, and cost efficiency.

- Collaborate with business stakeholders, data engineers, reporting teams, and technology leaders to translate requirements into scalable solutions.

- Define data modeling strategies, data governance practices, and data quality frameworks.

- Support integration of enterprise data sources, applications, and analytics platforms.

- Provide guidance on reporting and analytics architecture.

- Troubleshoot complex technical challenges and provide effective solutions.

- Mentor team members, conduct design reviews, and promote engineering best practices.

- Evaluate emerging data technologies and recommend improvements to existing platforms.

Required Skills & Qualifications :

- Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.

- 9+ years of experience in Cloud Architecture, Data Engineering, AI/ML, or Enterprise Technology Architecture.

- Strong experience designing and implementing enterprise cloud solutions.

- Expert-level knowledge of at least one major cloud platform.

- Strong understanding of cloud compute, storage, networking, and serverless services.

- Advanced knowledge of Docker and Kubernetes for microservices architecture and AI/ML model serving.

- Strong understanding of cloud security concepts including :

1. VPC design

2. IAM roles and policies

3. Zero Trust Architecture

4. Network security

5. Encryption at rest and in transit

- Experience designing scalable data platforms and data engineering solutions.

- Strong understanding of AI/ML lifecycle, model deployment, and production AI systems.

- Experience architecting Generative AI solutions using LLMs, AI services, and cloud AI platforms is preferred.

- Strong understanding of distributed systems and cloud-native architectures.

- Excellent communication, leadership, analytical, and problem-solving skills.