Data Engineer III: AI-Driven Data Platform

JPMorgan Chase & Co.

Glasgow

On-site

GBP 70,000 - 90,000

Full time

2 days ago
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Job summary

JPMorganChase is seeking a Data Engineer in the Corporate Technology team to build and deliver scalable data pipelines and analytics solutions that power AI initiatives across the firm.

You will maintain critical data architectures, collaborate with global teams, and drive improvements in data quality, governance, and operational stability while aligning with SDLC standards and security requirements.

Qualifications

  • Formal training or certification on software engineering concepts.
  • Experience in Risk Analytics space; knowledge of corporate bonds and securitisation products.
  • Proven experience integrating AI-assisted development tools into engineering workflows.
  • Experience with data governance, data quality, or analytics transformation programs.
  • Strong data profiling, analysis, and management using Python, R, SQL, Spark, DataBricks, and cloud platforms.
  • Understanding of data lineage concepts and experience with metadata management and data cataloguing.
  • Demonstrated experience using enterprise AI capabilities within the work environment to support data engineering workflows with strong validation habits and awareness of data sensitivity.
  • Hands-on 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.
  • 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.
  • 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 of existing data to support AI and NLQ usage, accelerate mesh data architecture adoption.
  • 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

Software engineering concepts
Risk Analytics
AI-assisted development tools
Data governance
Python
R
SQL
Spark
DataBricks
Cloud platforms
Data lineage
Metadata management
AI outputs validation
System design

Tools

Claude Code
Copilot
Graph databases
Vector databases
Metadata management platforms
Data cataloguing tools
LLM Ops
MLOps

Job description

JPMorganChase is seeking a Data Engineer in the Corporate Technology team to build and deliver scalable data pipelines and analytics solutions that power AI initiatives across the firm.

You will maintain critical data architectures, collaborate with global teams, and drive improvements in data quality, governance, and operational stability while aligning with SDLC standards and security requirements.

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