Data Layer AI Engineer

A Leading Banking & Financial Services Group is seeking an innovative Data Layer AI Engineer to join its Data Service Layer Delivery team. In this hybrid data engineering and analytics position, you will take responsibility for designing and implementing data mesh, data fabric, and semantic layer architectures. Furthermore, you will utilize data virtualization platforms such as Starburst or Denodo to execute federated querying across disparate cloud and on-prem systems. Consequently, this role is crucial for enabling decentralized data access and supporting enterprise BI reporting.

The Data Layer AI Engineer must combine extensive data modeling capabilities with hands-on experience in business intelligence tools (Power BI, Tableau) and cloud data platforms like Snowflake. Working within a cross-functional environment, you will leverage GitHub Copilot, Agentic AI, and RAG frameworks to accelerate pipeline delivery and testing. Therefore, the group is looking for an analytical professional who translates functional requirements into high-performing data integration designs. If you want to steer modern data mesh architectures, this position offers an ideal path.

Key Responsibilities

• Design, develop, and implement enterprise Data Mesh, Data Fabric, and semantic layer architectures across hybrid environments.
• Configure and manage data virtualization platforms (Starburst, Denodo) to execute high-speed federated queries across disparate data sources.
• Extract, transform, and load large volumes of structured and unstructured data into AWS data lakes and Snowflake data warehouses.
• Design, build, and deploy end-to-end report visualization solutions and executive dashboards in Power BI and Tableau.
• Implement robust Data Governance, Data Modeling, Row-Level Security (RLS), and data validation frameworks.
• Utilize GitHub Copilot, Agentic AI frameworks, Prompt Engineering, and RAG architectures to automate data integration workflows.
• Optimize and fine-tune data integration pipelines and Spark jobs to maintain high performance and low latency.

Requirements and Qualifications

• Bachelor’s degree in Information Technology, Computer Science, Software Engineering, or related technical disciplines.
• 5+ Years of experience in Data Virtualization, Data Mesh, or Federated Querying platforms (Denodo, Starburst, or open-source equivalents).
• 5+ Years of hands-on experience working as a Report Visualization Engineer with Power BI, Tableau, or modern reporting tools.
• 3+ Years of experience implementing Data Modeling, Data Governance, Enterprise Deployment Strategies, and Row-Level Security.
• 2+ Years of practical experience applying AI-assisted development tools (GitHub Copilot), LLMs, and Prompt Engineering.