JPMorgan Chase & Co.
Lead Software Engineer - Data/ Python/ AWS
JPMorgan Chase & Co., Jersey City, New Jersey, United States, 07390
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 at JPMorgan Chase within the Technology Division, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
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. Build scalable, robust, and secure data infrastructure solutions using Python on AWS. Architect and implement data pipelines and platform components using Apache Iceberg, Databricks, AWS Glue, and DuckDB. Use tools like AWS CloudFormation and Terraform to automate deployment and management of cloud resources. 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 Required qualifications, capabilities, and skills
Formal training or certification on Software Engineering concepts and 5+ years applied experience in Python and/ or Data engineering space. Hands-on practical experience delivering system design, application development, testing, and operational stability Strong proficiency in Python. Hands-on experience with AWS services (ECS, EKS, Lambda, S3, IAM, RDS, Fargate, Glue, etc.). Experience with data lake technologies, especially Apache Iceberg, Databricks, AWS Glue, and DuckDB. Experience with monitoring and alerting tools (CloudWatch, X-Ray, Prometheus, Grafana, Splunk). Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) In-depth knowledge of the financial services industry and their IT systems Practical cloud native experience Preferred qualifications, capabilities, and skills
AWS Certifications (e.g., Solutions Architect, Developer, Data Analytics) Experience with NLP, AI/ML workflow orchestration, or advanced analytics pipelines Prior experience in building enterprise-scale data platforms or analytics solutions Experience with containerization (Docker, Kubernetes) and cloud-native patterns
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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. Build scalable, robust, and secure data infrastructure solutions using Python on AWS. Architect and implement data pipelines and platform components using Apache Iceberg, Databricks, AWS Glue, and DuckDB. Use tools like AWS CloudFormation and Terraform to automate deployment and management of cloud resources. 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 Required qualifications, capabilities, and skills
Formal training or certification on Software Engineering concepts and 5+ years applied experience in Python and/ or Data engineering space. Hands-on practical experience delivering system design, application development, testing, and operational stability Strong proficiency in Python. Hands-on experience with AWS services (ECS, EKS, Lambda, S3, IAM, RDS, Fargate, Glue, etc.). Experience with data lake technologies, especially Apache Iceberg, Databricks, AWS Glue, and DuckDB. Experience with monitoring and alerting tools (CloudWatch, X-Ray, Prometheus, Grafana, Splunk). Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) In-depth knowledge of the financial services industry and their IT systems Practical cloud native experience Preferred qualifications, capabilities, and skills
AWS Certifications (e.g., Solutions Architect, Developer, Data Analytics) Experience with NLP, AI/ML workflow orchestration, or advanced analytics pipelines Prior experience in building enterprise-scale data platforms or analytics solutions Experience with containerization (Docker, Kubernetes) and cloud-native patterns
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