Data Engineer III - Python, Databricks, React

In this Data Engineer role, you will build and optimize data collection, storage and analytics solutions to support AI and analytics initiatives across the firm. You’ll maintain critical pipelines and architectures to enable secure, scalable data flows that power CIO, Treasury and Corporate Risk Management. You’ll work with cross-functional partners to drive innovation, governance, and operational excellence while shaping data products for AI-enabled decision making. This role offers the chance to impact data platform capabilities at scale within a collaborative, learning-focused culture.

• Make data available for AI and analytics initiatives by coordinating with use case owners and managing data dependencies
• Collaborate with business, technology and operations teams to understand data requests and enable rapid provisioning through AI for Data
• Promote AI-assisted development tools (Claude Code, Copilot) to accelerate delivery and improve developer productivity
• Prototype and deploy analytics and tooling using AI/ML and innovative approaches in partnership with stakeholders
• Implement and manage platform controls (access, security, compliance) in line with SDLC standards
• Identify data lineage and provenance to support governance, regulatory, and business needs; embed controls for safety and traceability
• Consolidate and reengineer data flows to drive efficiency and reduce risk
• Develop proactive data quality controls to shorten issue resolution time and improve client experience
• Showcase improvements in control environments and uplift metadata for AI/NLQ usage and Mesh data architecture

• Formal training or certification on software engineering concepts
• Experience in Risk Analytics space; knowledge of corporate bond investments and securitisation (e.g., CLO, CMBS, RMBS, ABS) is preferred
• Proven track record integrating AI-assisted development tools (Claude Code, Copilot)
• Experience in strategic or transformational data governance, data quality or analytics transformation programs
• Strong data profiling, analysis, and data management skills (Python, R, SQL, Spark, DataBricks, cloud platforms)
• Understanding of data lineage, metadata management, and data cataloguing
• Experience using enterprise AI capabilities to support data engineering workflows with validation and data sensitivity awareness
• Ability to review and validate AI-assisted outputs before use and escalate when uncertain
• Hands-on experience delivering system design, application development, testing, and operations stability

• Excellent interpersonal skills
• Ability to build cross-functional relationships
• Collaborative and results-driven
• Python
• R
• SQL