DE-Cloud Native Data Architect-AWS-GDSN02

Leadership and Stakeholders

• Engage client executives, business leaders, and technology stakeholders to define data-transformation strategies.
• Lead architecture review boards and direct solution architects, engineers, and technical leads.
• Mentor architects and engineering teams and support pre-sales, solution shaping, estimations, and proposals.

AI and Advanced Analytics

• Define architecture patterns for Generative AI and AI-driven analytics solutions.
• Drive adoption of AWS AI services and integration of GenAI capabilities into enterprise data platforms.
• Enable scalable AI and machine-learning solutions with data science teams, including LLM, RAG, vector database, semantic search, and knowledge graph architectures.

Experience and Core Qualifications

• Twelve to eighteen or more years of overall IT experience, including at least eight years in data and cloud architecture.
• Proven experience delivering enterprise-scale AWS data platforms and leading cloud modernization and data migration initiatives.
• Deep AWS data and analytics expertise covering S3, Redshift, Glue, Athena, EMR, Lambda, Lake Formation, Kinesis, and IAM.
• Extensive experience with data lakes, lakehouses, data warehouses, real-time platforms, data modeling, governance, security, quality, metadata, and lineage.
• Excellent stakeholder management, executive communication, and consulting skills.
• Bachelor’s degree in computer science, engineering, information technology, or a related field, or equivalent practical experience.

Preferred Qualifications

• AWS Solutions Architect Professional or AWS Data Analytics/Data Engineer certifications are highly desirable.
• Experience with Databricks, Snowflake, Apache Airflow, dbt, or Matillion is advantageous.
• Experience with data governance frameworks and compliance standards such as GDPR and HIPAA is relevant.

About EY Digital Engineering