National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Software Engineer II - Data Engineer, Python, SQL - Associate

JPMorgan Chase & Co.
London
1 month ago
Create job alert

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. 

As a Software Engineer II at JPMorgan Chase within Investment Banking, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Transaction Development is a centralised hub that generates buyer intelligence on Mid-Cap sponsors for JPM sell-sides, by leveraging deep knowledge of Sponsor investment strategies.

In order to execute at scale, a newly created technology team is embarking on a multi-year journey to provide enhanced digital capabilities to enable Transaction Development to take full advantage of the deep client relationships we have across GB and scaling proprietary idea generation

Job responsibilities 

Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture Contributes to software engineering communities of practice and events that explore new and emerging technologies Adds to team culture of diversity, equity, inclusion, and respect Build and maintain scalable data pipelines for batch and near real-time processing Optimize data workflows for performance, cost and reliability

 Required qualifications, capabilities, and skills 

Formal training or certification on software engineering concepts and proficient advanced experience in Data Engineering such as Python and SQL Hands-on practical experience in system design, application development, testing, and operational stability Proficient in coding in one or more languages Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages Overall knowledge of the Software Development Life Cycle Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security Practical cloud native experience Demonstrated knowledge of software applications and technical processes within a technical discipline (., cloud, artificial intelligence, machine learning, mobile, Strong Knowledge in Python and SQL Understanding of ETL best practices, data portioning and schema evolution Experience with data modelling and working with large-scale datasets and a solid understanding of data lake architecture and data warehousing

Preferred qualifications, capabilities, and skills 

Experience with AWS cloud services (. EC2, S3, IAM, Cloudwatch) Experience with Infrastructure as code (. Terraform) Experience working in Agile/Scrum teams

Related Jobs

View all jobs

Software Engineer II - Data Engineer, Python, SQL - Associate

Software Engineer III - Data Engineer - Python, SQL - Senior Associate

Senior Data Engineer

Applied Scientist II (Machine Learning), ITA - Automated Performance Evaluation

Software Manager

Data Engineering Lead

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.

The Ultimate Assessment-Centre Survival Guide for Machine Learning Jobs in the UK

Assessment centres for machine learning positions in the UK are designed to reflect the complexity and collaboration required in real-world ML projects. From psychometric assessments and live model-building tasks to group data science challenges and behavioural interviews, recruiters evaluate your statistical understanding, coding skills, communication and teamwork. Whether you specialise in deep learning, reinforcement learning or NLP, this guide offers a step-by-step approach to excel at every stage and secure your next ML role.