At a Glance
- Tasks: Lead the development of data pipelines and solutions for an innovative banking experience.
- Company: Join JP Morgan Chase, a global leader in financial services with a focus on digital transformation.
- Benefits: Competitive salary, diverse work environment, and opportunities for professional growth.
- Other info: Be part of a diverse team committed to inclusion and innovation.
- Why this job: Make a real impact in transforming digital banking for millions of customers.
- Qualifications: Experience in data engineering, Python coding, and cloud technologies required.
The predicted salary is between 80000 - 100000 £ per year.
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 Senior Lead Data Engineer at JPMorgan Chase within the International Consumer Bank, you will be part of a team that plays a crucial role in this initiative, dedicated to delivering an outstanding banking experience to our customers. 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 banking functions and products, providing opportunities to build data pipelines and reporting capabilities for functional areas such as finance and business management, treasury operations, financial crime prevention, regulatory reporting and analytics. We collaborate with product teams such as card payments, electronic payments, lending, customer onboarding, core banking, and insurance to understand their product data models and deliver tailored data solutions that meet business needs.
- Deliver end-to-end data pipeline solutions on cloud infrastructure leveraging the latest technologies and best industry practices.
- Structure software for easy understanding, testing, and evolution.
- Optimize data writing and reading for our needs.
- Monitor performance, identifying and solving problems effectively and ensure systems are reliable and easy to operate.
- Formal training or certification in data engineering concepts and applied experience.
- Recent hands-on professional experience as a data engineer.
- Experience coding in a recent version of Python.
- Experience designing and implementing effective tests (unit, component, integration, end-to-end, performance, etc.).
- Excellent written and verbal communication skills in English.
- Experience with data transformation frameworks and data pipeline orchestration tools.
- Experience managing large volumes of data and optimizing data processing.
- Understanding of event-based architecture, data streaming, and messaging frameworks.
- Ability to coach team members on coding practices, design principles, and implementation patterns.
- Experience with AWS cloud technologies.
- Experience with data governance frameworks.
- Understanding of incremental data processing and versioning.
- Understanding of RESTful APIs and web technologies.
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.
