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
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