Data Engineer II

Job 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 Lead Data Engineer - Vice President 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. You will work in a collaborative environment as part of a diverse, inclusive, and geographically distributed team. We are seeking individuals who are solution oriented, with a curious mindset, a passion for collaboration, 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 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.
Job responsibilities -

• Develop and implement processes and procedures to identify, monitor, and mitigate data risks within the product.

• Design and implement complex, scalable solutions to efficiently process data, ensuring consistent and timely delivery and availability. Focus on building robust systems that can handle large volumes of data with minimal downtime.

• Develop solutions using Agile DevOps methodologies and continuous integration/continuous deployment (CI/CD) practices on public cloud platforms.

• Create reusable frameworks with a strong emphasis on quality and long-term sustainability.

• Collaborate with key partners to enhance understanding of data usage within the business. Serve as a subject matter expert on the content and application of data in the product and related business areas.

• Support the Data Analytics & Insight team by identifying and integrating necessary data into analytics platforms.

• Document and enforce requirements for data accuracy, completeness, and timeliness within the product.

• Contribute to a team culture that values diversity, opportunity, inclusion, and respect.

Required qualifications, capabilities and skills

• Bachelor degree in Computer Science, Engineering, Information Systems or related disciplines

• Minimum 3 years of experience in data engineering and professional experience working in an agile, dynamic and customer facing environment

• Recent hands-on professional experience (actively coding) working as a data engineer (back-end software engineer considered)

• Understanding of distributed systems and cloud technologies (AWS, GCP, Azure, etc.)

• Understanding of data streaming and scalable data processing frameworks (Kafka, Spark Structured Streaming, Flink, Beam etc.)

• Experience with SQL (any dialect) and Data tools (ie. Dbt, Glue) and Working understanding of NoSQL databases

• Experience in the all stages of software development lifecycle (requirements, design, architecture, development, testing, deployment, release and support)

• Experience with large scale datasets , data lake and data warehouse technologies on at least TB scale (ideally PB scale of datasets) with at least one of {Redshift, Snowflake, BigQuery}

• Experience in Infrastructure as Code (ideally Terraform) for Cloud based data infrastructure

• Demonstrated expertise in Python programming, as well as hands-on experience with data processing technologies including Spark or PySpark.

Preferred qualifications, capabilities, and skills-

• Experience with a scheduling system (Step Function, Airflow etc.)

• Understanding of (distributed and non-distributed) data structures, caching concepts, CAP theorem

• Understanding of security frameworks / standards and privacy

• Desired - experience in automating deployment, releases and testing in continuous integration, continuous delivery pipelines

• A solid approach to writing unit level tests using mocking frameworks, as well as automating component, integration and end-to-end tests

• Experience with containers and container-based deployment environment (Docker, Kubernetes, etc.)