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 | Data Technology
Columbus, OH, United States
Live, first seen by us 77 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 postingDesign, develop and optimize large-scale ETL data pipelines
Build modular Python applications with logging and automated testing
Develop distributed data processing solutions in PySpark
Implement and support Control-M or Airflow workflow orchestration
Design and manage Iceberg or Delta Lake data lake architectures
From the employer’s posting
Design, develop, and optimize large-scale ETL (Extract Transform Load) data pipelines.
Build high-quality Python applications using modular code, reusable components, logging, and automated testing.
Develop and maintain distributed data processing solutions using PySpark.
Implement and support workflow orchestration using Control-M or Apache Airflow (MWAA).
Design and manage modern data lake architectures utilizing Iceberg and/or Delta Lake.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Aug 27, 202677 days ago
- Recorded sightings
- 244
- Last seen by us
- Nov 12, 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 77
Up longer than most. 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.
- Java
- Python
- SQL
- AWS
- dbt
- Delta Lake
- Kafka
- Snowflake
- Airflow
- PySpark
Where the posting names them
- Formal training or certification on software engineering concepts and 5+ years applied experience with a strong focus on data engineering. - Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages – Python (primary) & Java (secondary) - Hands-on experience with PySpark or other distributed data processing frameworks.
- Design, develop, and optimize large-scale ETL (Extract Transform Load) data pipelines. - Build high-quality Python applications using modular code, reusable components, logging, and automated testing. - Develop and maintain distributed data processing solutions using PySpark.
- Experience with Snowflake administration and development. - Strong SQL skills and experience with modern database technologies. - 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.
- Implement and support workflow orchestration using Control-M or Apache Airflow (MWAA). - Develop cloud-native solutions leveraging AWS services, including Glue, Athena, Lambda, and CloudWatch. - Design and manage modern data lake architectures utilizing Iceberg and/or Delta Lake.
- Experience with workflow orchestration platforms such as Control-M or Apache Airflow (MWAA). - Expertise with AWS data services, including Glue, Athena, CloudWatch, and Lambda. - Knowledge of modern open table formats such as Iceberg and/or Delta Lake.
- Hands-on experience with PySpark or other distributed data processing frameworks. - Strong expertise in DBT (Data Build Tool) and modern ETL (Extract Transform Load) development practices. - Experience with workflow orchestration platforms such as Control-M or Apache Airflow (MWAA).
- Develop cloud-native solutions leveraging AWS services, including Glue, Athena, Lambda, and CloudWatch. - Design and manage modern data lake architectures utilizing Iceberg and/or Delta Lake. - Administer and optimize Snowflake environments, including streams, tasks, roles, and warehouses.
- Expertise with AWS data services, including Glue, Athena, CloudWatch, and Lambda. - Knowledge of modern open table formats such as Iceberg and/or Delta Lake. - Experience with Snowflake administration and development.
Preferred qualifications, capabilities, and skills - Experience with Kafka, Flink, or other streaming technologies. - Familiarity with AI/ML technologies including LLMs, prompt engineering, vector search, and responsible AI practices.
- Design and manage modern data lake architectures utilizing Iceberg and/or Delta Lake. - Administer and optimize Snowflake environments, including streams, tasks, roles, and warehouses. - Participate in code reviews and champion engineering best practices, testing standards, and CI/CD processes.
- Knowledge of modern open table formats such as Iceberg and/or Delta Lake. - Experience with Snowflake administration and development. - Strong SQL skills and experience with modern database technologies.
- Large scale end-to-end testing design and validation. - Implement and support workflow orchestration using Control-M or Apache Airflow (MWAA). - Develop cloud-native solutions leveraging AWS services, including Glue, Athena, Lambda, and CloudWatch.
- Strong expertise in DBT (Data Build Tool) and modern ETL (Extract Transform Load) development practices. - Experience with workflow orchestration platforms such as Control-M or Apache Airflow (MWAA). - Expertise with AWS data services, including Glue, Athena, CloudWatch, and Lambda.
- Build high-quality Python applications using modular code, reusable components, logging, and automated testing. - Develop and maintain distributed data processing solutions using PySpark. - Large scale end-to-end testing design and validation.
- Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages – Python (primary) & Java (secondary) - Hands-on experience with PySpark or other distributed data processing frameworks. - Strong expertise in DBT (Data Build Tool) and modern ETL (Extract Transform Load) development practices.
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
This is your chance to change the path of your career and work at one of the world's leading financial institutions.
As a Lead Software Engineer – Data Engineering at JPMorgan Chase within the Consumer & Community Banking/Data Products team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products 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.
Job Responsibilities:
-
Design, develop, and optimize large-scale ETL (Extract Transform Load) data pipelines.
-
Build high-quality Python applications using modular code, reusable components, logging, and automated testing.
-
Develop and maintain distributed data processing solutions using PySpark.
-
Large scale end-to-end testing design and validation.
-
Implement and support workflow orchestration using Control-M or Apache Airflow (MWAA).
-
Develop cloud-native solutions leveraging AWS services, including Glue, Athena, Lambda, and CloudWatch.
-
Design and manage modern data lake architectures utilizing Iceberg and/or Delta Lake.
-
Administer and optimize Snowflake environments, including streams, tasks, roles, and warehouses.
-
Participate in code reviews and champion engineering best practices, testing standards, and CI/CD processes.
-
Leverage approved AI-assisted development tools while ensuring secure, responsible, and compliant software delivery.
Required qualifications, capabilities, and skills
-
Formal training or certification on software engineering concepts and 5+ years applied experience with a strong focus on data engineering.
-
Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages – Python (primary) & Java (secondary)
-
Hands-on experience with PySpark or other distributed data processing frameworks.
-
Strong expertise in DBT (Data Build Tool) and modern ETL (Extract Transform Load) development practices.
-
Experience with workflow orchestration platforms such as Control-M or Apache Airflow (MWAA).
-
Expertise with AWS data services, including Glue, Athena, CloudWatch, and Lambda.
-
Knowledge of modern open table formats such as Iceberg and/or Delta Lake.
-
Experience with Snowflake administration and development.
-
Strong SQL skills and experience with modern database technologies.
-
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.
Preferred qualifications, capabilities, and skills
-
Experience with Kafka, Flink, or other streaming technologies.
-
Familiarity with AI/ML technologies including LLMs, prompt engineering, vector search, and responsible AI practices.
-
Experience using AI-assisted software development tools such as GitHub Copilot, Claude, or similar technologies.
-
Financial services industry experience and understanding of large-scale enterprise data environments.
-
Experience mentoring engineers and leading technical delivery initiatives.
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.