Job
Description
You thrive on diversity and creativity, and we welcome individuals who share our vision of making a lasting impact. Your unique combination of design thinking and experience will help us achieve new heights. As a Data Engineer II at JPMorgan Chase within the Commercial Investment Bank Payments Technology team, you are part of an agile team that works to enhance, design, and deliver the data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. As an emerging member of a data engineering team, you execute data solutions through the design, development, and technical troubleshooting of multiple components within a technical product, application, or system, while gaining the skills and experience needed to grow within your role. Job responsibilities Collaborate with all of JPMorgan s lines of business and functions to delivery software solutions. Experiment, Architect, develop and productionize efficient Data pipelines, Data services and Data platforms contributing to the Business. Design and implement highly scalable, efficient and reliable data processing pipelines and perform analysis and insights to drive and optimize business result. Organizes, updates, and maintains gathered data that will aid in making the data actionable Demonstrates basic knowledge of the data system components to determine controls needed to ensure secure data access Adds to team culture of diversity, equity, inclusion, and respect Required qualifications, capabilities, and skills Formal training or certification on large scale technology program concepts and 2+ years applied experience in Data Technologies. Experienced programming skills with Java and Python. Experience across the data lifecycle, building Data frameworks, working with Data lakes. Experience with Batch and Real time Data processing with Spark or Flink Basic knowledge of the data lifecycle and data management functions Advanced at SQL (e.g., joins and aggregations) Working understanding of NoSQL databases Significant experience with statistical data analysis and ability to determine appropriate tools to perform analysis Basic knowledge of data system components to determine controls needed Good knowledge / experience on infrastructure as code. Preferred qualifications, capabilities, and skills Cloud computing Amazon Web Service, Docker, Kubernetes, Terraform Experience in big data technologies Hadoop, Hive, Spark, Kafka. Experience in distributed system design and development
