Software Engineer III - Databricks

About the role

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.

Responsibilities

• Provides technical leadership across design, development, and troubleshooting for complex, multi-domain solutions; establishes 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; drives 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; champions 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; models 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.

Requirements

• 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 ECS, EMR, Lambda, EC2, 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 within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated 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 and effective usage within team practices.

Preferred Qualifications

• Background with machine learning frameworks, MLOps practices, and end-to-end ML lifecycle management (feature pipelines, model registry, monitoring, drift detection).
• Experience with the Python ML ecosystem (pandas, NumPy) and platforms such as Databricks for data engineering and model development at scale.
• Experience with ERWIN for data modeling.
• Familiarity with TensorFlow.
• Familiarity with data modeling and query optimization.

Benefits

• Competitive total rewards package including base salary, commission-based pay, and/or discretionary incentive compensation (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.

About Us

JPMorgan Chase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses, and many of the world's most prominent corporate, institutional, and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years, and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing, and asset management.

About The Team

Our professionals in Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers, and employees up for success.