Backend Python/Databricks Software Engineer III

JPMorganChase is a financial institution transforming how financial data is engineered, processed, and delivered at scale. The Software Engineer III will design, build, and maintain scalable Python backend and Databricks data engineering solutions, develop reliable financial data pipelines, and collaborate with cross-functional teams to support enterprise financial reporting and analytics.

Responsibilities

Execute software solutions, design, development, and technical troubleshooting with the ability to think beyond routine or conventional approaches to build solutions or break down complex technical problems

Create secure and high-quality production code and maintain algorithms that run synchronously with appropriate systems, with a focus on Python backend development and PySpark-based data processing

Build, deploy, and support scalable data engineering modules on Databricks, ensuring reliable performance, maintainability, and alignment with platform architecture standards

Leverage 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; contribute learnings and reusable patterns to improve broader team effectiveness

Apply 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

Produce architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development

Gather, analyze, synthesize, and develop visualizations and reporting from large, diverse financial data sets in service of continuous improvement of software applications and systems

Proactively identify hidden problems and patterns in data and use these insights to drive improvements to coding hygiene and system architecture

Participate in code reviews, providing and incorporating constructive feedback to continuously elevate code quality and engineering standards across the team

Collaborate with product managers, architects, and cross-functional engineering teams to translate finance business requirements into scalable technical solutions

Preferred

Experience with Apache Spark, Kafka, or similar distributed data processing frameworks in a large-scale enterprise environment

Familiarity with cloud-based data platforms and services, particularly AWS (e.g., S3, Glue, Lambda, or equivalent)

Exposure to infrastructure-as-code or pipeline orchestration tools such as Apache Airflow, Terraform, or similar

Experience working within financial services or highly regulated enterprise data environments

Knowledge of data governance, data quality, or metadata management practices within a finance or analytics context

Apache Spark

Apache Kafka

Distributed data processing

Large-scale enterprise environments

Cloud data platforms

AWS

Amazon S3

AWS Glue

AWS Lambda

Infrastructure as code

Pipeline orchestration

Apache Airflow

Terraform

Financial services experience

Regulated data environments

Data governance

Data quality management

Metadata management

Finance analytics

Benefits

Commission-based pay and/or discretionary incentive compensation for eligible roles, paid in the form of cash and/or forfeitable equity

Comprehensive health care coverage

On-site health and wellness centers

A retirement savings plan

Backup childcare

Tuition reimbursement

Mental health support

Financial coaching

Company

Global financial institution offering banking, asset management, and advisory services

New York, New York, USA

https://www.jpmorganchase.com/

Founded in 2000

10001+ employees

Qualifications

Formal training or certification on software engineering concepts and 3+ years applied experience

Hands-on practical experience in system design, application development, testing, and operational stability

Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages

Proficiency in Python backend development with hands-on experience building and optimizing PySpark data pipelines in production environments

Demonstrated experience with Databricks, including module development, deployment, and ongoing operational support

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

Overall knowledge of the Software Development Life Cycle

Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security

Experience with Apache Spark, Kafka, or similar distributed data processing frameworks in a large-scale enterprise environment

Familiarity with cloud-based data platforms and services, particularly AWS (e.g., S3, Glue, Lambda, or equivalent)

Exposure to infrastructure-as-code or pipeline orchestration tools such as Apache Airflow, Terraform, or similar

Experience working within financial services or highly regulated enterprise data environments

Knowledge of data governance, data quality, or metadata management practices within a finance or analytics context

Required skills

Python, PySpark, Databricks, SQL, System Design, Application Development, Software Testing, AI-Assisted Software Development, Secure Coding, CI/CD

Experience

3+ years