Software Engineer III-Databricks

Benefits and culture

• Base salary determined by role, experience, skill set and location
• Commission-based pay and/or discretionary incentive compensation, paid in cash and/or forfeitable equity
• Comprehensive health care coverage
• On-site health and wellness centers
• Retirement savings plan
• Backup childcare
• Tuition reimbursement
• Mental health support
• Financial coaching

The team emphasizes a culture of diversity, opportunity, inclusion, and respect, with a commitment to proactive learning in AI, ML, and emerging technologies.

Role overview

In this Software Engineer III role focused on Databricks, you will join JPMorgan Chase within the Corporate Sector's Enterprise Technology team. You will be a seasoned member of an agile group dedicated to designing and delivering trusted, market-leading technology products in a secure, stable, and scalable manner. The position involves delivering critical technology solutions across multiple domains to support the firm’s business objectives.

Responsibilities

• Provide technical leadership across design, development, and troubleshooting for complex, multi-domain solutions; establish engineering standards and best practices for the team
• Develop secure, high-quality code in Python and/or Java; perform reviews and mentor engineers to improve code quality and maintainability
• Construct data pipelines using Databricks ETL
• Build and productionize cloud-based ML pipelines; lead model deployment and operationalization with Data Science and SRE/Platform teams
• Own MLOps workflows; coordinate infrastructure and production changes with SRE to ensure resiliency, observability, and security across the ML lifecycle
• Apply SDLC tooling and automation to accelerate delivery velocity and reliability; champion CI/CD and cloud-native practices
• Collaborate with Product Owners and business stakeholders to translate requirements into scalable solutions aligned to CCB Finance objectives
• Cultivate a team culture that values diversity, opportunity, inclusion, and respect; model proactive learning in AI/ML and emerging technologies
• Leverage enterprise-authorized AI coding assist tools to improve code quality, delivery speed, and productivity on complex deliverables, while validating outputs through peer review, automated testing, and secure coding standards; share learnings and reusable patterns with the team
• Utilize knowledge of the SDLC toolchain, including AI-assisted development and automation capabilities, to maximize the value delivered by automation

Requirements

• Formal training or certification in software engineering with at least three years of practical experience
• Hands-on experience in software engineering, system design, application development, testing, and operational stability
• Proficiency in Python and a strong foundation in secure data practices
• Hands-on Databricks experience covering 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 using AWS services such as ECS, EMR, Lambda, EC2, and SageMaker
• Experience with PySpark, Kafka, Terraform, and Kubernetes for data processing, streaming, IaC, and container orchestration
• Database experience with Oracle and/or Cassandra
• Familiarity with CI/CD, application resiliency, security best practices, Agile/Scrum methodologies, and SDLC automation tools
• Hands-on experience using enterprise-authorized AI-assisted software development tools, with the ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe usage within team practices

Technologies

• Python
• Java
• Databricks
• Delta Lake
• Unity Catalog
• Workflows
• Repos/notebooks
• SQL Warehouses
• AWS ECS
• AWS EMR
• AWS Lambda
• AWS EC2
• AWS SageMaker
• PySpark
• Kafka
• Terraform
• Kubernetes
• Oracle
• Cassandra

About JPMorgan Chase

JPMorgan Chase is a longstanding financial institution delivering innovative solutions to consumers, small businesses, and a broad range of corporate and government clients. With a history spanning more than 200 years, the firm is a leader across investment banking, consumer and commercial banking, payments, and asset management.

About the team

Our Corporate Functions span finance and risk, human resources, and marketing. These teams support the broader organization by enabling successful operations for clients, customers, and colleagues alike.