Lead Software Engineer - Databricks​/Snowflake​/AWS

Job 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 JPMorgan Chase within the Corporate Technology - Consumer and Community Banking Risk Technology team, 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.

• 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 using the syntax of at least one programming language with limited guidance in maintaining efficient algorithms that integrate seamlessly with relevant systems
• 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
• Implements and manages data solutions using Snowflake, including data modeling, performance tuning, and secure data sharing
• Develops workflows and ETL pipelines using Python, Databricks and Spark to optimize data processing and transformation at scale
• Frequently utilizes SQL with understanding the role of No
  
  SQL databases in the marketplace, and applies Spark for distributed data processing and analytics
• Gathers, analyzes, and synthesizes large diverse data sets to develop visualizations and reporting that drives continuous improvement of software applications and systems
• Applies knowledge of tools within the Software Development Life Cycle toolchain to improve the value realized by automation
• Gathers, analyzes, and draws conclusions from large, diverse data sets to identify problems and contribute to decision‑making in service of secure, stable application development
• Adds to team culture of diversity, opportunity, inclusion and respect, as a lead on the team – driving projects independently and providing technical and architectural guidance with junior engineers

• Formal training or certification in software / data engineering concepts and 8+ years applied experience
• Hands‑on practical experience delivering system design, application development, testing, operational stability and statistical data analysis, including selecting appropriate tools and identifying data patterns
• Advanced in one or more programming language(s) and framework(s) (i.e., Python 3, ETL, Spark, Snowflake, Databricks, SQL, No
  
  SQL, Terraform‑based infrastructure deployments, etc.)
• Significant experience with data migration and platform migration for data projects, including planning, execution, and post‑migration support
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, Security, and proficient in all aspects of the Software Development Life Cycle
• Demonstrate experience leading effective use of approved AI‑assisted software development tools (e.g., for…