Technology CDAO - Solution Architect

JPMorgan Chase & Co.
London
2 months ago
Create job alert

If you are excited about shaping the future of technology and driving significant business impact in financial services, we are looking for people just like you. Join our team and help us develop game-changing, high-quality solutions.

As a Sr Solutions Architect at JPMorgan Chase within the Technology Chief Data Office (CDO), you are responsible for designing and overseeing the implementation of our Technical Data Lakehouse and developing software for our supporting services that meet both technical and business requirements. You will provide technical leadership and guidance to development teams, ensuring adherence to best practices in software development and architecture. Collaborating closely with stakeholders, they translate business needs into technical specifications and evaluate tools and technologies to recommend optimal solutions. The architect ensures system scalability, performance, and security, while also managing the integration of new systems with existing infrastructure. You will also create and maintain appropriate documentation, address technical issues, and stay updated with industry trends to drive innovation and continuous improvement in software solutions.

Job responsibilities 

Provides feedback and proposes improvements to architecture governance practices Guides evaluation of current technology and leads evaluation of new technologies using existing standards and frameworks Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors Creates complex and scalable coding solutions using appropriate software design frameworks Drives decisions that influence product design, application functionality, and technical operations and processes Serves as a function-wide subject matter expert in one or more areas of focus Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle Influences peers and project decision-makers to consider the use and application of leading-edge technologies Adds to team culture of diversity, equity, inclusion, and respect

Required qualifications, capabilities, and skills 

Formal training or certification on software engineering concepts and 5+ years applied experience Hands-on practical experience delivering system design, application development, testing, and operational stability Advanced in one or more programming language(s), applications, and architecture Advanced knowledge of software architecture, applications, and technical processes with considerable in-depth knowledge in one or more technical disciplines (., cloud, artificial intelligence, machine learning, mobile, Ability to tackle design and functionality problems independently with little to no oversight Exposure to cloud technologies (AWS or GCP) via hands on experience or certification  Hands-on experience in data lake or data warehouse and related technologies (. Spark, ETL, Databricks).

Preferred qualifications, capabilities, and skills

Hands on exposure to metadata process & technology as well as a background in data management and data quality Hands-on practical experience delivering system design, application development, testing, and operational stability

Related Jobs

View all jobs

Technology Advisory - IT Strategy and Architecture - Managers/Associate Partners

Contract Python Engineer

Machine Learning Engineer

Recovery Administrator - (Debt Sale & Due Diligence) - Banking*

Senior Data Scientist

Tax, Technology and Transformation - ERP Senior Manager 1

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Contract vs Permanent Machine Learning Jobs: Which Pays Better in 2025?

Machine learning (ML) has swiftly become one of the most transformative forces in the UK technology landscape. From conversational AI and autonomous vehicles to fraud detection and personalised recommendations, ML algorithms are reshaping how organisations operate and how consumers experience products and services. In response, job opportunities in machine learning—including roles in data science, MLOps, natural language processing (NLP), computer vision, and more—have risen dramatically. Yet, as the demand for ML expertise booms, professionals face a pivotal choice about how they want to work. Some choose day‑rate contracting, leveraging short-term projects for potentially higher immediate pay. Others embrace fixed-term contract (FTC) roles for mid-range stability, or permanent positions for comprehensive benefits and a well-defined career path. In this article, we will explore these different employment models, highlighting the pros and cons of each, offering sample take‑home pay scenarios, and providing insights into which path might pay better in 2025. Whether you’re a new graduate with a machine learning degree or an experienced practitioner pivoting into an ML-heavy role, understanding these options is key to making informed career decisions.

Machine‑Learning Jobs for Non‑Technical Professionals: Where Do You Fit In?

The Model Needs More Than Math When ChatGPT went viral and London start‑ups raised seed rounds around “foundation models,” many professionals asked, “Do I need to learn PyTorch to work in machine learning?” The answer is no. According to the Turing Institute’s UK ML Industry Survey 2024, 39 % of advertised ML roles focus on strategy, compliance, product or operations rather than writing code. As models move from proof‑of‑concept to production, demand surges for specialists who translate algorithms into business value, manage risk and drive adoption. This guide reveals the fastest‑growing non‑coding ML roles, the transferable skills you may already have, real transition stories and a 90‑day action plan—no gradient descent necessary.

Quantexa Machine‑Learning Jobs in 2025: Your Complete UK Guide to Joining the Decision‑Intelligence Revolution

Money‑laundering rings, sanctioned entities, synthetic identities—complex risks hide in plain sight inside data. Quantexa, a London‑born scale‑up now valued at US $2.2 bn (Series F, August 2024), solves that problem with contextual decision‑intelligence (DI): graph analytics, entity resolution and machine learning stitched into a single platform. Banks, insurers, telecoms and governments from HSBC to HMRC use Quantexa to spot fraud, combat financial crime and optimise customer engagement. With the launch of Quantexa AI Studio in February 2025—bringing generative AI co‑pilots and large‑scale Graph Neural Networks (GNNs) to the platform—the company is hiring at record pace. The Quantexa careers portal lists 450+ open roles worldwide, over 220 in the UK across data science, software engineering, ML Ops and client delivery. Whether you are a graduate data scientist fluent in Python, a Scala veteran who loves Spark or a solutions architect who can turn messy data into knowledge graphs, this guide explains how to land a Quantexa machine‑learning job in 2025.