We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Senior Vice President of Data Engineering at JPMorgan Chase within the Data Infrastructure department, your role will be to guide the strategic direction and execution of our data engineering initiatives. Your responsibilities will include promoting innovation and excellence in our data infrastructure, ensuring that our data operations are secure, scalable, and in line with the firm's strategic objectives. Your leadership will be crucial in enhancing our analytics capabilities and promoting a culture of data-promoten decision-making across the organization.

 

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.Conduct feasibility studies, capacity planning, and process redesign/re-engineering of complex integration solutions.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.

 

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.Mastery of SQL, including the ability to design and optimize complex queries and database structures.Deep understanding of NoSQL databases and their strategic applications within the industry.Proven track record in statistical data analysis and the ability to derive actionable insights from complex data sets.Experience in leading large-scale data engineering projects and implementing custom solutions to meet business objectives.Demonstrated ability to build and manage cloud-native data pipelines in AWS, with hands-on knowledge of AWS components.

 

Preferred qualifications, capabilities, and skills

AWS certifications are an added advantage.