Lead Data Engineer Lead Data Engineer

Join us as we embark on a journey of collaboration and innovation, where your unique skills and talents will be valued and celebrated. Together we will create a brighter future and make a meaningful difference.

As a Lead Data Engineer at JPMorgan Chase within the Consumer & Community Banking Team, you are an integral part of an agile team that works to enhance, build, and deliver data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. As a core technical contributor, you are responsible for maintaining critical data pipelines and architectures across multiple technical areas within various business functions in support of the firm s business objectives.

Job responsibilities

• Generates data models for their team using firmwide tooling, linear algebra, statistics, and geometrical algorithms
• Delivers data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way
• Implements database back-up, recovery, and archiving strategy
• Evaluates and reports on access control processes to determine effectiveness of data asset security with minimal supervision
• Adds to team culture of diversity, equity, inclusion, and respect
• Designing Database, infrastructure architecture disciplines, and business processes.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience in

  Amazon Aurora PostgreSQL

  Database Administration

  /Engineering.
• Administer, design, implement, and support highly available and scalable AWS RDBMS & Distributed database solutions.
• Experience in AWS Cloud Relational and NoSQL database management, including AWS Aurora PostgreSQL, AWS RDS, DynamoDB, data replication, and AWS monitoring tools.
• Implement data models, database designs, data access, and table maintenance codes.
• Maintain databases with high availability features using data partitioning and database replications.
• Resolve database performance, capacity, replication, and other data issues.
• Collaborate with Information Architects and Database Designers to implement the physical data model.
• Experience with Atlassian tools like Jira and Confluence.

Join us as we embark on a journey of collaboration and innovation, where your unique skills and talents will be valued and celebrated. Together we will create a brighter future and make a meaningful difference.

As a Lead Data Engineer at JPMorgan Chase within the Consumer & Community Banking Team, you are an integral part of an agile team that works to enhance, build, and deliver data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. As a core technical contributor, you are responsible for maintaining critical data pipelines and architectures across multiple technical areas within various business functions in support of the firm s business objectives.

Job responsibilities

• Generates data models for their team using firmwide tooling, linear algebra, statistics, and geometrical algorithms
• Delivers data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way
• Implements database back-up, recovery, and archiving strategy
• Evaluates and reports on access control processes to determine effectiveness of data asset security with minimal supervision
• Adds to team culture of diversity, equity, inclusion, and respect
• Designing Database, infrastructure architecture disciplines, and business processes.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience in

  Amazon Aurora PostgreSQL

  Database Administration

  /Engineering.
• Administer, design, implement, and support highly available and scalable AWS RDBMS & Distributed database solutions.
• Experience in AWS Cloud Relational and NoSQL database management, including AWS Aurora PostgreSQL, AWS RDS, DynamoDB, data replication, and AWS monitoring tools.
• Implement data models, database designs, data access, and table maintenance codes.
• Maintain databases with high availability features using data partitioning and database replications.
• Resolve database performance, capacity, replication, and other data issues.
• Collaborate with Information Architects and Database Designers to implement the physical data model.
• Experience with Atlassian tools like Jira and Confluence.