What are the responsibilities and job description for the Lead Software Engineer - Big Data & AWS position at JPMorgan Chase?
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As a Lead Software Engineer at JPMorganChase within COMMERCIAL & INVESTMENT BANK, 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
- Creates and 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
- Develops secure high-quality production code, and reviews and debugs code written by others
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.
- 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
- Processing and analyzing large datasets using Big Data technologies, including Apache Spark, across data platforms comprising of Redshift, SQL DB, RDS and Databricks.
- Setup and Configuration of AWS services such as S3, Databricks, Step Functions, EMR, Glue, Lambda, RDS, Step-Functions and API Gateway for scripting, automation, and orchestration of data workflows.
Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
- Development of semantic layer for data consumption using Iceberg tables and APIs.
- 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.)
- Identifying, implementing and optimizing AI-driven automation opportunities within technology lifecycle management.
- Well versed with AI and emerging technologies.