You have the opportunity to unleash your full potential at a world-renowned company and take the lead in shaping the future of technology.

As a Senior Manager of Data Engineering at JPMorgan Chase within the CCB, you serve in a leadership role by providing technical coaching and advisory for multiple technical teams, as well as anticipate the needs and potential dependencies of other data users within the firm. As an expert in your field, your insights influence budget and technical considerations to advance operational efficiencies and functionalities.

Job responsibilities

Architect and oversee the design of complex data solutions that meet diverse business needs and customer requirements. Guide the evolution of logical and physical data models to support emerging business use cases and technological advancements. Build and manage end-to-end cloud-native data pipelines in AWS, leveraging your hands-on expertise with AWS components. Build analytical systems from the ground up, providing architectural direction, translating business issues into specific requirements, and identifying appropriate data to support solutions. Work across the Service Delivery Lifecycle on engineering major/minor enhancements and ongoing maintenance of existing applications. Help others build code to extract raw data, coach the team on techniques to validate its quality, and apply your deep data knowledge to ensure the correct data is ingested across the pipeline. Guide the development of data tools used to transform, manage, and access data, and advise the team on writing and validating code to test the storage and availability of data platforms for resilience. Oversee the implementation of performance monitoring protocols across data pipelines, coaching the team on building visualizations and aggregations to monitor pipeline health. Coach others on implementing solutions and self-healing processes that minimize points of failure across multiple product features. Adds to team culture of diversity, equity, inclusion, and respect

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and 5+ years applied experience Extensive experience in managing the full lifecycle of data, from collection and storage to analysis and reporting. Proficiency in one or more large-scale data processing distributions such as JavaSpark along with knowledge on Data Pipeline (DPL), Data Modeling, Data warehouse, Data Migration and so-on. Hands-on practical experience in system design, application development, testing, and operational stability Proficient in coding in one or more modern programming languages Should have good hands-on experience with AWS services and its components along with good understanding on Kubernetes. Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages. Strong understanding of domain driven design, micro-services patterns, and architecture Overall knowledge of the Software Development Life Cycle along with experience with IBM MQ, Apache Kafka Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, LLMs etc.) Preferred qualifications, capabilities, and skills Familiarity with modern front-end technologies Experience designing and building REST API services using Java Exposure to cloud technologies - knowledge on Hybrid cloud architectures is highly desirable.