Lead Data Engineer - Python & AI-Driven Data Pipelines

JPMorgan Chase & Co.; Glasgow; On-site; GBP 90,000 - 140,000; Full time

Job summary

JPMorgan Chase & Co. in Glasgow seeks a Lead Data Engineer to shape data-driven innovation and deliver data collection, storage, access, and analytics solutions in a secure, scalable way for AI and analytics initiatives.

You will maintain critical data pipelines and architectures, lead data governance, and drive collaboration with stakeholders to accelerate delivery and improve operational efficiency across the firm.

Qualifications

• Formal training or certification on software engineering concepts and applied experience.
• Experience and awareness in working within Risk Analytics space; preferred knowledge of corporate bond investment assets and structured credit products such as securitisation (e.g., CLO, CMBS, RMBS, ABS).
• Proven experience integrating AI-assisted development tools into engineering workflows.
• Experience in strategic or transformational change initiatives, including data governance, data quality, or analytics transformation programs.
• Strong technical skills in data profiling, analysis, and data management using modern tools and environments (Python, R, SQL, Spark, DataBricks, cloud platforms).
• Understanding of data lineage concepts and experience with lineage analysis, metadata management, and data cataloguing.
• Excellent communication skills with the ability to convey complex technical concepts to diverse audiences, including executive leadership.
• Experience with data quality frameworks, including profiling, rule development, issue remediation, and preventative controls.
• Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support data engineering workflows with strong validation habits and awareness of data sensitivity.
• Ability to review and validate AI-assisted outputs (e.g., code, model/design summaries or operational checklists) before use, escalating when uncertain and following data handling requirements.
• Hands‑on practical experience delivering system design, application development, testing, and operational stability.

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 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
• Lead data quality issue root cause analysis using deep data profiling and advanced analytics techniques, then fix the cause and embed uplifted evergreen controls to prevent future failures
• Develop proactive controls to reduce the time from data quality issue identification to resolution, improving client experience and driving operational efficiency
• Demonstrate control environment improvements and reduction in toil through common tooling and frameworks; uplift the metadata (semantic layer) of existing data to support AI and Natural Language Query usage, accelerate adoption of Mesh data architecture, reduce consumer friction, and deliver data product prototypes
• Uses enterprise-authorized AI capabilities within the work environment to accelerate data platform and model design analysis and documentation, validating outputs and handling data according to sensitivity and security requirements
• Applies reuse-first, AI-assisted practices within delivery and operational routines, ensuring traceability/auditability and alignment to resiliency and security expectations

Skills

Data engineering

AI/ML tools

Team leadership

Data governance

Strong communication

Tools

Python

R

SQL

Spark

Databricks

Cloud platforms

Job description

JPMorgan Chase & Co. in Glasgow seeks a Lead Data Engineer to shape data-driven innovation and deliver data collection, storage, access, and analytics solutions in a secure, scalable way for AI and analytics initiatives.

You will maintain critical data pipelines and architectures, lead data governance, and drive collaboration with stakeholders to accelerate delivery and improve operational efficiency across the firm.