J.P. Morgan
Lead Software Engineer-Cloud Data/Python/Java/Spark
J.P. Morgan, Wilmington, Delaware, us, 19894
Overview
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Lead Software Engineer-Cloud Data/Python/Java/Spark at JPMorgan Chase within the Consumer and Community Banking's Home Lending and Servicing team, you will play a crucial role in an agile team dedicated to enhancing, building, and delivering reliable, market-leading technology products that are secure, stable and scalable. Job responsibilities Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems Develops secure high-quality production code, and reviews and debugs code written by others Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies Adds to team culture of diversity, opportunity, inclusion, and respect Architect, develop, and deploy scalable data pipelines and solutions on AWS using services such as S3, Redshift, Glue, EMR, Lambda, and Athena Create and optimize data models, build robust ETL processes, and ensure efficient ingestation, transformation, and storage Monitor, troubleshoot, and tune data pipelines and cloud resources for optimal performance, reliability, and cost efficiency Maintain comprehensive documentation of data architectures, processes and best practices; mentor junior engineers and share knowledge within the team Stay current with AWS advancements, evaluate new services and tools, and drive continuous improvement in cloud data engineering practices Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and 5+ years applied experience Hands-on practical experience delivering system design, application development, testing, and operational stability Hands-on professional experience in one or more programming language(s), including Java or Python, proficiency in Python, SQL, and at least one additional language (e.g. Java or Scala) for data engineering tasks Hands-on experience utilizing Apache Spark for large-scale data processing, including developing and optimizing data pipelines, performing real-time and batch analytics, and leveraging Spark’s libraries for machine learning and data transformation to drive actionable business insights. Experience with infrastructure automation tools such as AWS CloudFormation or Terraform Proficiency in all aspects of the Software Development Life Cycle Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security Demonstrated experience in system design, including architecting scalable and reliable solutions, selecting appropriate technologies, defining system components and their interactions, and ensuring alignment with business requirements and performance goals through detailed documentation and collaborative design reviews. Experience with AWS services related to data storage and management, such as AWS Aurora, DynamoDB, S3, and RDS Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) AWS Certifications Preferred qualifications, capabilities, and skills Extensive experience working with relational databases such as Oracle, MySQL, and SQL Server, including designing schemas, writing complex queries, optimizing performance, and ensuring data integrity for a variety of business applications. Snowflake experience is a plus Databricks experience is a plus
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We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Lead Software Engineer-Cloud Data/Python/Java/Spark at JPMorgan Chase within the Consumer and Community Banking's Home Lending and Servicing team, you will play a crucial role in an agile team dedicated to enhancing, building, and delivering reliable, market-leading technology products that are secure, stable and scalable. Job responsibilities Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems Develops secure high-quality production code, and reviews and debugs code written by others Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies Adds to team culture of diversity, opportunity, inclusion, and respect Architect, develop, and deploy scalable data pipelines and solutions on AWS using services such as S3, Redshift, Glue, EMR, Lambda, and Athena Create and optimize data models, build robust ETL processes, and ensure efficient ingestation, transformation, and storage Monitor, troubleshoot, and tune data pipelines and cloud resources for optimal performance, reliability, and cost efficiency Maintain comprehensive documentation of data architectures, processes and best practices; mentor junior engineers and share knowledge within the team Stay current with AWS advancements, evaluate new services and tools, and drive continuous improvement in cloud data engineering practices Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and 5+ years applied experience Hands-on practical experience delivering system design, application development, testing, and operational stability Hands-on professional experience in one or more programming language(s), including Java or Python, proficiency in Python, SQL, and at least one additional language (e.g. Java or Scala) for data engineering tasks Hands-on experience utilizing Apache Spark for large-scale data processing, including developing and optimizing data pipelines, performing real-time and batch analytics, and leveraging Spark’s libraries for machine learning and data transformation to drive actionable business insights. Experience with infrastructure automation tools such as AWS CloudFormation or Terraform Proficiency in all aspects of the Software Development Life Cycle Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security Demonstrated experience in system design, including architecting scalable and reliable solutions, selecting appropriate technologies, defining system components and their interactions, and ensuring alignment with business requirements and performance goals through detailed documentation and collaborative design reviews. Experience with AWS services related to data storage and management, such as AWS Aurora, DynamoDB, S3, and RDS Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) AWS Certifications Preferred qualifications, capabilities, and skills Extensive experience working with relational databases such as Oracle, MySQL, and SQL Server, including designing schemas, writing complex queries, optimizing performance, and ensuring data integrity for a variety of business applications. Snowflake experience is a plus Databricks experience is a plus
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