Lead Software Engineer

At JP Morgan Chase, we understand that customers seek exceptional value and a seamless experience from a trusted financial institution. That's why we launched Chase UK to transform digital banking with intuitive and enjoyable customer journeys. With a strong foundation of trust established by millions of customers in the US, we have been rapidly expanding our presence in the UK and soon across Europe. We have been building the bank of the future from the ground up, offering you the chance to join us and make a significant impact.

As a Lead Software Engineer- Back-end Engineer - Chase UK at JPMorgan Chase within the International Consumer Bank, you will play a crucial role in this initiative, dedicated to delivering an outstanding banking experience to our customers. You will work in a collaborative environment as part of a diverse, inclusive, and geographically distributed team. We are seeking individuals with a curious mindset and a keen interest in new technology. Our engineers are naturally solution-oriented and possess an interest in the financial sector and focus on addressing our customer needs. We work in teams focused on specific products and projects, providing opportunities to engage in areas such as fraud & financial crime prevention, identity services, money transfers, card payments, lending, customer onboarding, core banking, insurance products, rewards campaigns, and servicing innovations. reward campaigns, call-centre supporting innovations and more.

Job responsibilities:

• Deliver end-to-end solutions in the form of cloud-native microservices architecture applications leveraging the latest technologies and the best industry practices
• Design, build, and operate scalable batch and streaming data pipelines (ETL/ELT) to ingest, process, and curate data for operational and analytical use-cases.
• Work with Big Data technologies and patterns (e.g., distributed processing and large-scale datasets) to ensure performance, reliability, and cost efficiency and develop and maintain curated analytics datasets / data products that enable reporting, KPI measurement, and dashboarding for business stakeholders.
• Partner with business analysts and product teams to define metrics, ensure data quality/lineage, and create trusted datasets that power dashboards and self-serve analytics.
• Use domain modelling techniques to allow us to build best in class business products.
• Structure software so that it is easy to understand, test and evolve.
• Build solutions that avoid single points of failure, using scalable architectural patterns and develop secure code so that our customers and ourselves are protected from malicious actors.
• Promptly investigate and fix issues and ensure they do not resurface in the future and make sure our releases happen with zero downtime for our end-users.
• See that our data is written and read in a way that's optimized for our needs and keep an eye on performance, making sure we use the right approach to identify and solve problems.
• Support the products you've built through their entire lifecycle, including in production and during incident management
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.

Required qualifications, capabilities and skills

• Formal training or certification in software engineering concepts and applied professional experience.
• Recent hands-on professional experience as a back-end software engineer.
• Strong Java experience (recent versions).
• Strong testing experience (unit, component, integration, end-to-end, performance, etc.).
• Hands-on data engineering experience building and operating production-grade data pipelines (batch and/or streaming) and integrations.
• Experience with Big Data / distributed processing and large-scale datasets (e.g., Spark/Hadoop ecosystems or equivalent managed services).
• Strong SQL and experience with analytics data modelling (e.g., dimensional/semantic modelling, KPI definitions).
• Experience with data quality controls, observability, and operational support for data pipelines.
• Experience with cloud technologies, distributed systems, RESTful APIs, and web technologies.
• Knowledge of messaging frameworks and experience operating/supporting mission-critical applications, including security considerations.
• Understanding of data stores, including relational databases and excellent written and verbal English communication skills.

Preferred qualifications, capabilities and skills

• Experience in working in a highly regulated environment / industry
• Experience with AWS data services (e.g., S3, Glue, EMR, Athena, Redshift, Kinesis/MSK or equivalents) and cloud data lake / lakehouse patterns.
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
• Experience with orchestration and CI/CD for data pipelines (e.g., Airflow or similar) and versioned data transformations.
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
• Seasoned with cloud-native microservices architecture
• Proficient with AWS cloud technologies