Lead Data Engineer - Python, Databricks, React

In this Lead Data Engineer role within Corporate Technology, you will build and scale data collection, storage, access, and analytics solutions to support AI and analytics initiatives. You’ll maintain and improve critical pipelines and architectures across multiple domains to align with the firm’s business objectives. You will drive innovation, operational excellence, and provide technical leadership in a collaborative culture. The opportunity centers on shaping data-enabled solutions at scale while upholding security and governance. You’ll work closely with cross-functional teams to accelerate AI readiness and data-driven decision making.

• Make data available for AI and analytics initiatives by defining requirements and managing cross-product data delivery
• Collaborate with business, technology, and operations teams to accelerate data provisioning and support AI for Data deployments
• Promote AI-assisted development tools to boost delivery speed and developer productivity
• Prototype and deploy analytics and tooling using AI/ML and innovative approaches
• Implement and manage platform controls (access, security, compliance) in line with SDLC standards
• Provide transparency on bottlenecks, progress, and metrics to enable AI-ready data source adoption
• Identify data lineage and provenance to support governance and regulatory needs; embed evergreen controls for traceability
• Improve data flows through consolidation and reengineering to enhance efficiency and reduce risk
• Lead data quality root cause analysis and embed preventive controls to avoid recurring issues
• Develop proactive data quality controls to shorten issue resolution time and improve client experience
• Showcase improvements in control environments and reduce toil using common tooling; uplift metadata and enable AI/NLQ usage

• Formal training or certification in software engineering concepts
• Experience in Risk Analytics space; knowledge of corporate bond investments and securitisation products (e.g., CLO, CMBS, RMBS, ABS) preferred
• Experience integrating AI-assisted development tools into engineering workflows
• Experience with data governance, data quality, or analytics transformation programs
• Strong skills in data profiling, analysis, and management using Python, R, SQL, Spark, DataBricks, cloud platforms
• Understanding of data lineage, metadata management, and data cataloguing
• Excellent communication skills for diverse audiences including executives
• Experience with data quality frameworks and preventative controls
• Experience validating AI-assisted outputs and ensuring data handling compliance
• Hands-on experience delivering system design, application development, testing, and operations

• strong communication
• collaboration across global teams
• ability to balance strategic vision with pragmatic delivery
• Python
• R
• SQL