We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As a Software Engineer III - Databricks at JPMorgan Chase within the Corporate Sector's Enterprise Technology team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives. Job responsibilities

• Provides technical leadership across design, development, and troubleshooting for complex, multi-domain solutions; establish engineering standards and best practices for the team
• Writes secure, high-quality code in Python and/or Java; conducts reviews and mentors engineers to raise code quality and maintainability
• Builds data pipelines using Databricks ETL
• Builds and productionizes cloud-based ML pipelines; drive model deployment and operationalization in collaboration with Data Science and SRE/Platform teams
• Owns MLOps workflows; coordinates infrastructure and production changes with SRE; ensures resiliency, observability, and security across the ML lifecycle
• Applies SDLC tooling and automation to improve delivery velocity and reliability; champion CI/CD and cloud-native best practices
• Partners with Product Owners and business stakeholders to translate requirements into scalable solutions aligned to CCB Finance objectives
• Fosters a team culture of diversity, opportunity, inclusion, and respect; model proactive learning in AI/ML and emerging technologies
• Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.

g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness

• 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 Required qualifications, capabilities, and skills
• Formal training or certification on software engineering concepts and 3+ years applied experience
• Hands-on experience in software engineering, system design, application development, testing, and operational stability
• Proficiency in Python; strong grounding in secure data practices
• Hands-on Databricks experience across Delta Lake, Unity Catalog, Workflows, Repos/notebooks, and SQL Warehouses, including cluster configuration and optimization
• Cloud engineering experience building ML pipelines and deploying models to production with AWS services such as EC.

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