Senior Software Engineer - AI-Driven DevOps & Data Platform

JPMorgan Chase; Columbus (OH); On-site; USD 120,000 - 150,000; Full time

Job summary

JPMorganChase in Columbus, OH is seeking a Lead Software Engineer in DevOps & Infrastructure to join the Employee Platforms, Workforce Experience Tech team. You will contribute to secure, scalable software across the SDLC, collaborating in an agile setting to design and deliver modern data-driven solutions.

You will work on production-grade code, AI-assisted tooling, and architecture reviews, driving performance, security, and reliability across enterprise data systems.

Qualifications

• Formal training or certification in software engineering concepts and 5+ years of applied experience.
• Hands-on experience designing, developing, and operating ETL/ELT data pipelines.
• Strong understanding of data warehousing concepts and query optimization.
• Experience with enterprise data tools and modern programming languages.

Responsibilities

• Executes creative software solutions and troubleshoots complex problems beyond routine approaches.
• Develops secure, high-quality production code and reviews peers' work.
• Drives adoption of AI-assisted engineering practices to improve quality and speed.
• Applies SDLC tools and AI-assisted development capabilities to improve automation.
• Identifies opportunities to automate recurring issues for stability.
• Leads evaluation sessions with vendors and internal teams on architecture and applicability.

Skills

ETL/ELT data pipelines

Python

SQL

Data warehousing

CI/CD

AI-assisted development

Tools

Databricks

Apache Spark

Delta Lake

Lakeflow

CI/CD tools

Job description

JPMorganChase in Columbus, OH is seeking a Lead Software Engineer in DevOps & Infrastructure to join the Employee Platforms, Workforce Experience Tech team. You will contribute to secure, scalable software across the SDLC, collaborating in an agile setting to design and deliver modern data-driven solutions.

You will work on production-grade code, AI-assisted tooling, and architecture reviews, driving performance, security, and reliability across enterprise data systems.