Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Validation Senior Lead Software Engineer

JPMorgan Chase & Co.
Glasgow
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

LLM / NLP Data Scientist Lead - Vice President - ESG

Senior Data Analyst (R-18263)

Global Data Science Manager - MMM

Senior Data Analyst (Statistical Programming)

Senior Analytics Data Engineer – Snowflake & DBT (Contract)

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As a Data Validation Senior Lead Software Engineer at JPMorgan Chase within the Data Products Engineering team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

Job responsibilities

Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors Develops secure and high-quality production code, and reviews and debugs code written by others Drives decisions that influence the 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 the team culture of diversity, equity, inclusion, and respect

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and advanced applied experience. Hands-on practical experience delivering system design, application development, testing, and operational stability Advanced in one or more programming language(s) such as Core Java Advanced knowledge of software 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 Practical cloud native experience Experience in Data Quality Rules management using external vendor tools like Drules, Signavio, Camunda or any other similar Business Rules Engine.  Hands on experience in data profiling, data governance and overall data quality framework at large enterprise scale applications. Hands on experience with metadata management solutions, decouple business & data pipelines. Deeper knowledge of enterprise data catalogue solution and how to leverage it to harvest data quality rules.  Hands on experience with AWS including setting up EKS and leveraging context apocopate AWS services, Spark, EMR and UI frameworks. 

Preferred qualifications, capabilities, and skillsProficiency in automation and continuous delivery methods Additional knowledge of front-end technologies . React / Tuxedo/JS  Prior experience with Databricks, Data modelling, ETL.

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.

The Best Free Tools & Platforms to Practise Machine Learning Skills in 2025/26

Machine learning (ML) has become one of the most in-demand career paths in technology. From predicting customer behaviour in retail to detecting fraud in banking and enabling medical breakthroughs in healthcare, ML is transforming industries across the UK and beyond. But here’s the truth: employers don’t just want candidates who have read about machine learning in textbooks. They want evidence that you can actually build, train, and deploy models. That means practising with real tools, working with real datasets, and solving real problems. The good news is that you don’t need to pay for expensive software or courses to get started. A wide range of free, open-source tools and platforms allow you to learn machine learning skills hands-on. Whether you’re a beginner or preparing for advanced roles, you can practise everything from simple linear regression to deploying deep learning models — at no cost. In this guide, we’ll explore the best free tools and platforms to practise machine learning skills in 2025, and how to use them effectively to build a portfolio that UK employers will notice.

Top 10 Skills in Machine Learning According to LinkedIn & Indeed Job Postings

Machine learning (ML) is at the forefront of innovation, powering systems in finance, healthcare, retail, logistics, and beyond in the UK. As organisations leverage ML for predictive analytics, automation, and intelligent systems, demand for skilled practitioners continues to grow. So, which skills are most in demand? Drawing on insights from LinkedIn and Indeed, this article outlines the Top 10 machine learning skills UK employers are looking for in 2025. You'll learn how to demonstrate these capabilities through your CV, interviews, and real-world projects.

The Future of Machine Learning Jobs: Careers That Don’t Exist Yet

Machine learning (ML) has become one of the most powerful forces reshaping the modern world. From voice assistants and recommendation engines to fraud detection and medical imaging, it underpins countless applications. ML is no longer confined to research labs—it powers business models, public services, and consumer technologies across the globe. In the UK, demand for machine learning professionals has risen dramatically. Organisations in finance, retail, healthcare, and defence are embedding ML into their operations. Start-ups in Cambridge, London, and Edinburgh are pioneering innovations, while government-backed initiatives aim to position the UK as a global AI leader. Salaries for ML engineers and researchers are among the highest in the tech sector. Yet despite its current importance, machine learning is only at the beginning of its journey. Advances in generative AI, quantum computing, robotics, and ethical governance will reshape the profession. Many of the most vital machine learning jobs of the next two decades don’t exist today. This article explores why new careers will emerge, the roles likely to appear, how today’s roles will evolve, why the UK is well positioned, and how professionals can prepare now.