Pay
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,239 postings in the last year. Stated ranges, not salaries paid.
Lead Software Engineer: Data Engineering
Columbus, OH, United States
Live, first seen by us 42 days ago- Pay
- Pay not listedSimilar roles state $127K–$190K
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
Before you apply
- Employer’s visa record
- 272 H-1B petitions approved in fiscal 2024 and 2025For the employer as a whole. This posting doesn’t say whether the role is sponsored. US Citizenship and Immigration Services.
What you’ll work on
Full postingArchitect and deliver data pipelines across ingestion, transformation, curation and consumption
Build reusable Python and/or Scala libraries, frameworks and pipeline templates
Own operational excellence: data quality, monitoring, alerting, SLAs and incident root-cause analysis
Drive SDLC standards for CI/CD, testing, secure coding and code reviews
Lead and mentor engineers and partner with product, analytics and security teams
From the employer’s posting
Architects and delivers data platforms and pipelines across ingestion, transformation, curation, and consumption on AWS and Databricks using Spark and Delta.
Builds reusable Python and/or Scala libraries, frameworks, pipeline templates, and automation.
Owns operational excellence, including data quality, monitoring and alerting, SLAs, incident triage and RCA, and performance and cost optimization.
Drives SDLC standards covering CI/CD, testing strategy, secure coding, resiliency patterns, and design and code reviews.
Leads and mentors engineers and partners with product, analytics, and security teams to deliver roadmaps and execution.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 30, 202642 days ago
- Recorded sightings
- 199
- Last seen by us
- Nov 12, 2026
- Employer says posted
- Sep 15, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 42
Similar jobs usually come down between day 6 and day 56.
Well past JPMorgan Chase’s usual: its jobs come down by about day 15.
From 13,338 similar postings that came down, and 983 of JPMorgan Chase’s. Coming down is not always a hire.
JPMorgan Chase is hiring
362 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring has slowed
- Takes jobs down at a usual pace
- 3% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- Scala
- AWS
- Databricks
- Delta Lake
- Spark
Where the posting names them
- Architects and delivers data platforms and pipelines across ingestion, transformation, curation, and consumption on AWS and Databricks using Spark and Delta. - Builds reusable Python and/or Scala libraries, frameworks, pipeline templates, and automation. - Owns operational excellence, including data quality, monitoring and alerting, SLAs, incident triage and RCA, and performance and cost optimization.
- Hands-on practical experience delivering system design, application development, testing, and operational stability - Strong Python coding skills, and deep experience with Databricks and Spark. - Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As an Engineering Lead at JPMorganChase within Employee Platforms, you are an integral part of an agile team responsible for the hands-on delivery and architecture of secure, stable, scalable data engineering solutions on AWS and Databricks. As a core technical contributor, you own technical direction, develop critical components, drive production reliability, and deliver trusted technology products in support of the firm’s business objectives. Job responsibilities
- Develops secure and high-quality production code, and reviews and debugs code written by others. - Architects and delivers data platforms and pipelines across ingestion, transformation, curation, and consumption on AWS and Databricks using Spark and Delta. - Builds reusable Python and/or Scala libraries, frameworks, pipeline templates, and automation.
- Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security - Strong experience with AWS and modern lakehouse and data platform patterns. - Proven technical leadership through architecture decisions, mentoring, and cross-team influence.
Preferred qualifications, capabilities, and skills - AWS certification and/or Databricks certification. - Experience with streaming architectures, including event-driven ingestion, near-real-time processing, and operational support for monitoring, alerting, and recovery.
Your next step
Complete your application on jpmc.fa.oraclecloud.com. The employer’s form will show what is required.
Applying through Oracle Recruiting
- Applying starts by asking for your email address.
- Each employer sets which files it accepts, so read the note beside the upload field.
Already applied? Track this application
About JPMorgan Chase
- People
- About 318,512 in 2025.Annual report (SEC Form 10-K)
- Company
- Listed as JPM.
- Layoff notices
- Notices this year and last cover 152 people. The latest was filed March 23, 2026.State WARN notices
Demand for Data Engineer roles
New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Job description
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As an Engineering Lead at JPMorganChase within Employee Platforms, you are an integral part of an agile team responsible for the hands-on delivery and architecture of secure, stable, scalable data engineering solutions on AWS and Databricks. As a core technical contributor, you own technical direction, develop critical components, drive production reliability, and deliver trusted technology products in support of the firm’s business objectives.
Job responsibilities
As an Engineering Lead at JPMorganChase within Employee Platforms, you are an integral part of an agile team responsible for the hands-on delivery and architecture of secure, stable, scalable data engineering solutions on AWS and Databricks. As a core technical contributor, you own technical direction, develop critical components, drive production reliability, and deliver trusted technology products in support of the firm’s business objectives.
Job responsibilities
-
Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
- Develops secure and high-quality production code, and reviews and debugs code written by others.
- Architects and delivers data platforms and pipelines across ingestion, transformation, curation, and consumption on AWS and Databricks using Spark and Delta.
- Builds reusable Python and/or Scala libraries, frameworks, pipeline templates, and automation.
- Owns operational excellence, including data quality, monitoring and alerting, SLAs, incident triage and RCA, and performance and cost optimization.
- Drives SDLC standards covering CI/CD, testing strategy, secure coding, resiliency patterns, and design and code reviews.
- Leads and mentors engineers and partners with product, analytics, and security teams to deliver roadmaps and execution.
- Uses enterprise-authorized GenAI developer tools such as GitHub Copilot and Claude Code to accelerate refactoring, test generation, and documentation with strong validation and controls.
- Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
- Applies 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.
- Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
Required qualifications, capabilities, and skills
- Formal training or certification on data engineering concepts with architecture and production ownership concepts and 5+ years applied experience
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Strong Python coding skills, and deep experience with Databricks and Spark.
- Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
- Proficient in all aspects of the Software Development Life Cycle
- Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- Strong experience with AWS and modern lakehouse and data platform patterns.
- Proven technical leadership through architecture decisions, mentoring, and cross-team influence.
Preferred qualifications, capabilities, and skills
- AWS certification and/or Databricks certification.
- Experience with streaming architectures, including event-driven ingestion, near-real-time processing, and operational support for monitoring, alerting, and recovery.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Columbus, OH, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.