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Lead Data Engineer - PySpark/Databricks/SQL/AWS

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

What you’ll work on

Full posting
  • Deliver secure, stable, scalable data collection, storage, access and analytics platform solutions

  • Generate data models using firmwide approaches and statistical and geometric algorithms

  • Implement database back-up, recovery and archiving strategy

  • Evaluate and report on access control processes for data asset security

  • Use enterprise-authorized AI tools to speed up design docs, validating outputs before use

From the employer’s posting
Delivers data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way
Generates data models for the team using firmwide approaches, linear algebra, statistical and geometrical algorithms
Implements database back-up, recovery, and archiving strategy
Evaluates and reports on access control processes to determine effectiveness of data asset security with minimal supervision
Uses enterprise-authorized AI capabilities within the work environment to accelerate data platform and model design analysis and documentation, validating outputs
Apply at JPMorgan Chase

Posting record

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Actively hiringFirst seen by us 4 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Oct 30, 20264 days ago
Recorded sightings
4
Last seen by us
Nov 2, 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

Pay

$127K–$190K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 2,133 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 4

Early. Similar jobs usually come down between day 5 and day 54.

From 10,704 similar postings that came down. Coming down is not always a hire.

JPMorgan Chase is hiring

413 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring at a steady pace
  • Takes jobs down at a usual pace
  • 3% of open jobs were reposted
Hiring record

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
  • SQL
  • AWS
  • Databricks
  • NoSQL
  • PySpark
Where the posting names them
- Formal training or certification on data engineering concepts and 5+ years applied experience - Strong experience with Python, PySpark, Databricks, SQL, AWS and AI automation - Proficient in and experience across the data lifecycle
Join us as we embark on a journey of collaboration and innovation, where your unique skills and talents will be valued and celebrated. Together we will create a brighter future and make a meaningful difference. As a Lead Data Engineer - PySpark/Databricks/SQL/AWS at JPMorganChase within the Corporate Technology, you are an integral part of an agile team that works to enhance, build, and deliver data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. As a core technical contributor, you are responsible for maintaining critical data pipelines and architectures across multiple technical areas within various business functions in support of the firm’s business objectives. Job responsibilities
- Ability to review and validate AI-assisted outputs (e.g., model/design summaries or operational checklists) before use, escalating when uncertain and following data handling requirements. - Working experience with both relational and NoSQL databases - Experience implementing database back-up, recovery, and archiving strategy

Your next step

Complete your application on jpmc.fa.oraclecloud.com. The employer’s form will show what is required.

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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

View original posting ↗

Join us as we embark on a journey of collaboration and innovation, where your unique skills and talents will be valued and celebrated. Together we will create a brighter future and make a meaningful difference. 

As a Lead Data Engineer - PySpark/Databricks/SQL/AWS at JPMorganChase within the Corporate Technology, you are an integral part of an agile team that works to enhance, build, and deliver data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. As a core technical contributor, you are responsible for maintaining critical data pipelines and architectures across multiple technical areas within various business functions in support of the firm’s business objectives. 

Job responsibilities
  • Delivers data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way
  • Uses enterprise-authorized AI capabilities within the work environment to accelerate data platform and model design analysis and documentation, validating outputs and handling data according to sensitivity and security requirements.
  • Generates data models for the team using firmwide approaches, linear algebra, statistical and geometrical algorithms
  • Implements database back-up, recovery, and archiving strategy
  • Evaluates and reports on access control processes to determine effectiveness of data asset security with minimal supervision
  • Applies reuse-first, AI-assisted practices within delivery and operational routines (e.g., backup/recovery validation and access control review support), ensuring traceability/auditability and alignment to resiliency and security expectations.
 
Required qualifications, capabilities, and skills
  • Formal training or certification on data engineering concepts and 5+ years applied experience 
  • Strong experience with Python, PySpark, Databricks, SQL, AWS and AI automation
  • Proficient in and experience across the data lifecycle
  • Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support data engineering workflows with strong validation habits and awareness of data sensitivity.
  • Ability to review and validate AI-assisted outputs (e.g., model/design summaries or operational checklists) before use, escalating when uncertain and following data handling requirements.
  • Working experience with both relational and NoSQL databases
  • Experience implementing database back-up, recovery, and archiving strategy
  • Proficient knowledge of linear algebra, statistical and geometrical algorithms
 
Preferred qualifications, capabilities, and skills
  • Emerging technologies
Source details

View original posting ↗

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Location & working pattern

Wilmington, DE, United States

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