Job Description

We have an exciting and rewarding opportunity for you to advance your software engineering career. Join us to build innovative data solutions and accelerate engineering productivity Guidelines.docx.

As a Senior Data Engineer at JPMorgan Chase within the Corporate Technology team, you design and deliver robust, scalable data products using Databricks/Spark on AWS.. You help modernize data processing platforms and pioneer LLM-assisted development, contributing to secure and reliable solutions that drive business impact Guidelines.docx.

Job responsibilities

• Design and deliver Databricks/Spark pipelines on AWS using Delta Lake/Lakehouse patterns
• Build and maintain secure, high-quality production code in Python/PySpark aligned to enterprise security best practices
• Implement CI/CD-first delivery using infrastructure-as-code (Terraform/CloudFormation) and automated testing for repeatable deployments
• Produce architecture and design artifacts for complex applications, ensuring performance, resiliency, and security constraints are met
• Gather, analyze, and synthesize data to drive continuous improvement of software applications and systems
• Proactively identify hidden problems and patterns in data to improve coding hygiene and system architecture

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and eight years applied experience
• Hands-on practical experience in system design, application development, testing, and operational stability
• Proficient in coding in Python and PySpark
• Experience in developing, debugging, and maintaining code in a large corporate environment with Databricks/Spark and database querying languages
• Overall knowledge of the Software Development Life Cycle
• Solid understanding of agile methodologies, CI/CD, application resiliency, and security
• Demonstrated ability to use Copilot/LLM-assisted workflows effectively while maintaining quality and security through review and automation

Preferred qualifications, capabilities, and skills

• Experience with agentic automation or LLM tooling patterns (e.g., task-oriented agents for incident triage, deployment validation, data quality checks, or developer enablement) Raw Posting.docx
• Familiarity with Data Mesh, Airflow, and/or ThoughtSpot Raw Posting.docx
• AWS and/or Databricks certifications (e.g., AWS SAA / Developer Associate / Data Analytics Specialty, Databricks certification) Raw Posting.docx
• Design, build, and operate scalable Databricks/Spark data products on AWS, with a strong emphasis on Agentic AI patterns, LLM-enabled developer workflows, and Copilot-assisted delivery