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# Software Engineer III- Python, PySpark, ETL, AWS

- **Company:** JPMorgan Chase & Co.
- **Location:** Jersey City, NJ, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Artificial Intelligence, Amazon Web Services, Amazon S3, Software Applications, Microsoft Azure, Big Data, Cloud Computing, Continuous Integration, Extract Transform Load (ETL), Data Visualization, Database Queries, Software Debugging, DevOps, Python (Programming Language), Machine Learning, NoSQL, Performance Tuning, Ansible, Tensorflow, Standard Sql, Software Engineering, Software Systems, Systems Architecture, Pytorch, Large Language Models, Snowflake, Generative AI, Gitlab, Cloudformation, Pyspark, Scikit Learn, Information Technology, Production Code, Maintaining Code, Machine Learning Operations, Terraform, Amazon Elastic Mapreduce (EMR), Jenkins, Databricks, Programming Languages
- **Published:** May 14, 2026
- **Apply:** https://www.careerjet.com/jobad/us02282399c2a8587bc18dd0cb3f4161eb

## About the Role

* Formal training or certification in software engineering concepts with 3+ years of applied experience
 * Hands-on practical experience in system design, application development, testing, and operational stability
 * Extensive hands-on Python and PySpark experience
 * Experience with major cloud platforms (AWS/Azure/GCP) and big-data services (e.g., AWS EMR, Redshift, Lambda, S3)
 * Experience developing multi model LLM systems, GenAI tools, ML Model lifecycle, AI coding assist tools, and cloud-native ML Ops pipelines and frameworks
 * Familiar with Python-based ML libraries (e.g., Scikit-learn, PyTorch, TensorFlow) and ability to work with data scientists to operationalize models
 * Proficiency with DevOps/CI/CD (e.g., Jenkins/GitLab) plus strong SQL/NoSQL skills, including performance tuning/optimization
 * Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
 * Overall knowledge of the Software Development Life Cycle
 * Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
 * Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)

Preferred qualifications, capabilities, and skills

 * Familiarity with data visualization tools and data integration patterns
 * Experience with cloud lake house platforms like Snowflake and/or Databricks
 * In-depth knowledge of the financial services industry and their IT systems
 * Experience with declarative infra provisioning tools like Terraform, Ansible or CloudFormation

## Description

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Software Engineer III- Python, PySpark, ETL, AWS at JPMorganChase within the Asset and Wealth Management Technology team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology solutions in the business intelligence, AI and reporting space 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., Executes 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 to build unified data model, business intelligence, reporting and AI/ML solutions to ensure seamless integration into business workflows.
 * Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
 * Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
 * Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
 * Contributes to software engineering communities of practice and events that explore new and emerging technologies
 * Adds to team culture of diversity, opportunity, inclusion, and respect


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