Lead Software Engineer - Python/Data/PySpark/AWS
Posted Updated
Description
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 JPMorganChase within the Consumer & Community Banking, JPMWM Tech, 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:
As a Lead Software Engineer at JPMorganChase within the Consumer & Community Banking, JPMWM Tech, 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 software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
- Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
- Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
- Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
- Contributes to software engineering communities of practice and events that explore new and emerging technologies
- Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
- Adds to team culture of diversity, equity, inclusion, and respect
- Detects, troubleshoots and Resolves Production issues in an Enterprise multi-environment settings using advanced observability tools
Required qualifications, capabilities, and skills:
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Hands-on practical experience in system design, application development, testing, and operational stability
- Proficient in coding in one or more languages - Java, Python
- Proficient in private and public Cloud hosted Platform - Pivotal Cloud, AWS. In-depth knowledge is a must for AWS ECS, S3, SQS, SNS, Lambda, Glue, pySpark, cloudwatch
- Experienced in SRE and Observability tools - Splunk, Dynatrace and Datadog
- Proficient in Oracle, DB2 and AW Aurora Postgress Database. Hands on experience writing SQL is a must
- Hands on experience in Software Development tools and CI/CD tools - Jenkins, Spinnaker, IntelliJ, Bitbucket
- Hands on experience in IAC - Terraform
- Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
- Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
Preferred qualifications, capabilities, and skills:
- Overall knowledge of the Software Development Life Cycle
- Familiarity with modern front-end technologies
- Experience in Data Pipeline design and development
- Experience in Cloud migration projects
- Experience in AWS Glue and PySPark
Skills
- Agile
- AI
- Aurora
- Automation
- AWS
- Aws Glue
- Bitbucket
- CI/CD
- Cloud
- CloudWatch
- Data Pipelines
- Datadog
- Db2
- Dynatrace
- ECS
- Infrastructure as Code
- IntelliJ IDEA
- Java
- Jenkins
- Lambda
- Machine Learning
- Observability
- Oracle
- PySpark
- Python
- Root Cause Analysis
- S3
- Secure Coding
- SNS
- Splunk
- SQL
- SQS
- SRE
- Terraform
- Test Automation