Lead Data Engineer: AI-Driven Data Platform Leader

JP Morgan Chase; Glasgow; On-site; GBP 62,000 - 102,000; Full time

Job summary

JPMorganChase in the United Kingdom seeks a data engineering lead for risk analytics and AI-enabled data platforms. You will shape data governance, data lineage, and quality programs while delivering scalable data pipelines that empower AI and analytics initiatives.

You will collaborate with cross-functional teams to integrate AI tooling, manage data dependencies, and ensure SDLC compliance. The role emphasizes strong communication with executives and stakeholders.

Qualifications

• Formal training or certification on software engineering concepts and applied experience.
• Experience in Risk Analytics; familiarity with corporate bond investments and structured credit products.
• Proven experience integrating AI-assisted development tools into engineering workflows.
• Experience in data governance, data quality, or analytics transformation programs.
• Strong technical skills in data profiling, analysis, and data management using Python, R, SQL, Spark and cloud platforms.
• Understanding of data lineage concepts and experience with lineage analysis, metadata management, and data cataloguing.
• Excellent communication, able to convey complex concepts to executives, including leadership.
• Experience with data quality frameworks, profiling, and preventative controls.
• Experience using enterprise AI capabilities to support data engineering with strong validation habits.
• Ability to review AI outputs before use, escalating when uncertain and following data handling requirements.
• Hands-on experience delivering system design, application development, testing, and operational stability.
• Hands-on experience with data lineage tools and techniques, including graph & vector databases and metadata management platforms.
• Hands-on experience with LLM Ops, MLOps, and AI/ML platform deployment at scale.
• Familiarity with business-led analytics delivery models and rapid prototyping frameworks.
• Experience with AI governance, prompt engineering, and integrating AI tools into SDLC.
• Experience with AI/ML technologies and their application to data management challenges.
• Understanding of agile and product management methodologies and experience working in agile teams.
• Ability to multi-task in a fast-paced environment and operate independently with minimal supervision; strong judgment with the ability to balance strategic vision with pragmatic, incremental delivery.
• Experience building and growing capabilities and developing talent in data science or data management teams.
• Excellent interpersonal skills and ability to build strong working relationships with business, technology, and control stakeholders across global teams.

Responsibilities

• Make data available for AI and analytics initiatives, working closely with use case owners to define requirements, manage product dependencies, and support agile routines that oversee cross-product data dependencies and prioritize delivery.
• Collaborate with business, technology, and operations partners to understand data requests and accelerate provisioning through deployment of AI for Data.
• Drive adoption of AI-assisted development tools (e.g., Claude Code, Copilot) to accelerate delivery and improve developer productivity.
• Partner with business and technology teams to rapidly prototype and deploy analytics and tooling, leveraging AI/ML and innovative approaches.
• Implement and manage platform controls, including access, security, and compliance, ensuring all data and AI solutions meet firmwide SDLC standards.
• Provide transparency and drive executive visibility into bottlenecks, progress, performance metrics, and adoption tracking in making AI-ready and critical data sources available for innovation.
• Identify the lineage and provenance of critical data assets to support governance, regulatory, and business requirements; embed evergreen controls on data flows to improve safety, transparency, and traceability.
• Drive insight into areas of efficiency and risk through consolidation and reengineering of data flows.

Skills

Software engineering concepts

AI-assisted development tools

Data governance

Data quality

Communication

Agile/product management

Data lineage

Tools

Python

SQL

Spark

DataBricks

Cloud platforms

LLM Ops

MLOps

Metadata management

Graph databases

Job description

JPMorganChase in the United Kingdom seeks a data engineering lead for risk analytics and AI-enabled data platforms. You will shape data governance, data lineage, and quality programs while delivering scalable data pipelines that empower AI and analytics initiatives.

You will collaborate with cross-functional teams to integrate AI tooling, manage data dependencies, and ensure SDLC compliance. The role emphasizes strong communication with executives and stakeholders.