Principal Data Engineer, AWS

Responsibilities

• Define and drive platform strategy for capital provisioning modelling
• Architect and build cloud-native platforms (AWS) supporting model and data workloads
• Provide thought leadership and contribute to the design of technical solutions and consumption patterns, including data security and data management
• Design solutions that consume and operationalise enterprise data marketplace assets
• Lead engineering patterns for model and ML deployment, orchestration and monitoring
• Drive migration from legacy platforms to strategic, governed environments
• Ensure alignment with Model Risk Management, regulatory and audit requirements, including: Data lineage and traceability, Reproducibility of model outputs, Strong controls and validation
• Partner with modelling teams to productionise models and improve reliability and performance
• Influence architecture and engineering decisions across crews and domains
• Set and uplift engineering standards and practices
• Mentor engineers and contribute to a high-performing engineering culture

Requirements

• Have strong experience building cloud-native data and model platforms at scale
• Have experience productionising models or ML workloads
• Have experience in building frameworks and tools that can significantly improve engineering productivity
• Understand data integrity, reconciliation, and accuracy in financial systems
• Can influence across teams and align stakeholders on technical direction
• Have a natural drive to educate, communicate, and coordinate with different internal stakeholders and consultants

Core Competencies

Demonstrates expertise in architecting and building cloud-native platforms on AWS, with a focus on capital provisioning modeling and data management. Proven ability to lead engineering practices, mentor teams, and ensure compliance with regulatory requirements while enhancing model performance and reliability.

Highest-signal resume keywords

• Cloud-Native Platform Development
• Model Productionisation
• Data Security and Management
• Engineering Standards and Practices
• Stakeholder Alignment and Communication

Hard Skills

• Cloud-Native Development
• Model Deployment
• Data Management
• Data Lineage
• Model Risk Management
• Framework Development
• Data Integrity
• ML Workloads
• Orchestration
• Monitoring

Soft Skills

• Thought Leadership
• Mentoring
• Influencing
• Communication
• Collaboration

Industry Keywords

• Capital Provisioning
• Financial Systems
• Regulatory Compliance
• Audit Requirements
• Model Outputs

Tools & Technologies

• AWS
• Data Marketplace Assets
• Engineering Tools