JPMorgan Chase—Data Domain Architect Assoc

Job description

Description: 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 Data Domain Architect within the International Consumer Bank (ICB), you will play a pivotal role in advancing the integration of Chase and JPMorgan Personal Investing data platforms to support business growth and scalability. You will contribute to the design and delivery of high-performing, scalable data products and datasets within a medallion-architected data lakehouse environment. These solutions will power analytics, reporting, operational processes, data science initiatives, and regulatory use cases across the organization. Working within a global, cross-functional team of engineers, analysts, and product managers, you will help define data architecture standards, translate business requirements into technical solutions, and ensure the quality, performance, and governance of critical data assets. Job Responsibilities - Partner with business stakeholders, analysts, and platform users to understand data requirements, business objectives, and functional needs. - Design scalable, reliable, and performant data architectures and domain models that support enterprise data products and analytical workloads. - Collaborate with data engineering teams to develop and enhance data pipelines, datasets, and lakehouse solutions aligned with architectural standards and best practices. - Validate and test data models, transformations, and enhancements to ensure accuracy, quality, and alignment with business requirements. - Establish and maintain technical documentation, data definitions, lineage information, and user-facing documentation supporting platform capabilities. - Implement and manage data quality controls, validation frameworks, reconciliations, and operational runbooks to ensure data integrity and platform reliability. - Drive continuous improvement and innovation by identifying opportunities to optimize data structures, processes, and platform performance. - Support Agile delivery practices and contribute to the successful execution of strategic data initiatives across global teams. Required Qualifications, Capabilities, and Skills - Minimum 3 years of experience in Data Analytics, Data Engineering, Data Architecture, Business Analysis, or a related discipline. - Demonstrated experience working with SQL, ETL processes, data warehousing concepts, and large-scale data platforms. - Strong understanding of data modeling, data lifecycle management, and analytical data structures. - Ability to translate complex business problems into scalable technical solutions and actionable requirements. - Experience collaborating effectively within Agile and cross-functional teams while managing responsibilities independently. - Strong written and verbal communication skills with the ability to engage stakeholders across varying levels of technical expertise. - Proven analytical, problem-solving, and decision-making skills. - Self-motivated with the ability to manage priorities and deliver results in a fast-paced environment. - Passion for driving innovation, operational excellence, and adoption of data best practices. Preferred Qualifications, Capabilities, and Skills - Experience within Financial Services, Wealth Management, Investment Management, Brokerage, or Consumer Banking environments. - Knowledge of modern cloud-based data platforms, lakehouse architectures, and enterprise data ecosystems. - Familiarity with data governance, regulatory reporting, and data quality management frameworks. - Experience supporting analytical use cases including business intelligence, data science, operational reporting, and commercial analytics. - Bachelor's degree in Computer Science, Information Systems, Business Analytics, Engineering, or a related field.