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JPMorgan Chase & Co.

Data Engineer III - Python, Databricks, React

Glasgow
Posted about 21 hours ago
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Join us as a Data Engineer and help drive data innovation at JPMorganChase. You will collaborate with talented colleagues to deliver impactful solutions that power AI and analytics initiatives across the firm. We value your expertise, encourage growth, and support your journey to make a lasting impact. Experience a culture that celebrates diverse perspectives and fosters continuous learning.

Job Summary

As a Data Engineer in the Corporate Technology team supporting CIO, Treasury & Corporate Risk Management, you will enhance, build, and deliver data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. You will maintain critical data pipelines and architectures across multiple technical areas, supporting the firm’s business objectives. Your work will drive innovation, operational excellence, and team success, contributing to a collaborative culture that values your ideas and technical skills.

Job 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
  • 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 (semantic layer) of existing data to support AI and Natural Language Query (NLQ) 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 (e.g., backup/recovery validation and access control review support), ensuring traceability/auditability and alignment to resiliency and security expectations

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I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Required Qualifications, Capabilities, and Skills

  • Formal training or certification on software engineering concepts
  • 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 (e.g., Claude Code, Copilot, or similar) 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
  • 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

Preferred Qualifications, Capabilities, and Skills

  • 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/ML governance, prompt engineering, and integrating AI tools into SDLC
  • Experience with AI/ML technologies and their application to data management challenges (e.g., automated data profiling, metadata enrichment)
  • Understanding of agile and product management methodologies and experience working in agile teams
  • Excellent interpersonal skills and ability to build strong working relationships with business, technology, and control stakeholders across global teams

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J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success.

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Skills

Python
Databricks
React
SQL
Spark
Data Engineering
Data Pipelines
Data Governance
AI/ML
Cloud Platforms
Data Lineage
Metadata Management
Software Engineering
Risk Analytics
Agile Methodologies
Prompt Engineering

Location

Glasgow, Scotland, United Kingdom

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