Lead Software Engineer, Python, Databricks and AWS

JPMorgan Chase

Confirmed live 2 days ago Low trust

Quick summary

Work type: On-site
Location: Jersey City, NJ
Posted: 44 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

How this pay compares to similar roles

Similar $202k

$180k most similar roles pay here $230k

This listing doesn't post a salary. Most similar roles pay $192,050–$211,200.

Based on 240 similar postings.

Employer

About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 1117 open roles on FindRole.

Listed pay typically runs $186,160–$215,000 across 7 roles with salary data.

Most-posted roles

View all roles at JPMorgan Chase

At a glance

TL;DR · Lead Software Engineer, Python, Databricks and AWS

Role Posting Log in to save

Lead Software Engineer - Python, Databricks and AWS joins the Corporate Technology team to build and deliver secure, scalable technology products. As a core technical contributor, you will architect lake house layers, design domain data products, and implement resilient batch and streaming ingestion from AWS sources into Databricks using Delta Live Tables. You will manage production workloads through Databricks Workflows, ensure data governance via Unity Catalog, and optimize Spark performance and cluster sizing. The role involves leading engineering standards, mentoring team members in Spark best practices, and integrating AI-assisted engineering tools for code quality and testing. Technical requirements include expertise in Python, Delta Lake, S3, IAM, and Terraform for infrastructure as code. You will solve complex data engineering challenges including CDC, schema evolution, and automated CI/CD pipelines while ensuring high availability through robust monitoring and incident response.

Skills

Databricks Spark Delta Lake AWS Terraform S3 CI/CD Structured Streaming Unity Catalog Data Engineering CDC

What you'll do

Architect the lake house by designing bronze, silver, and gold data layers and domain products.
Implement resilient batch and streaming data ingestion from AWS sources into Databricks.
Build maintainable pipelines using Delta Live Tables with modular structures, testing, and documentation.
Productionize workloads using Databricks Workflows with robust retries, checkpointing, and idempotency.
Enforce data governance including least privilege, PII classification, auditing, and lineage metadata.
Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality and delivery speed.
Optimize Spark and Delta workloads for performance while managing cluster sizing and warehouse spend.
Lead technical design reviews and mentor engineers on Spark and Databricks best practices.

What we're looking for

Formal training or certification in software engineering concepts and 5+ years of hands-on Software Development Life Cycle experience.
Strong data engineering experience with a proven track record of leading delivery and architecture for multi-team data platforms.
Hands-on experience building and operating a Databricks Lakehouse hosted in AWS.
Deep experience with Delta Lake, including ACID tables, partitioning, schema evolution, and Spark performance tuning on Databricks.
Experience with streaming and batch pipelines using Structured Streaming, incremental processing, and backfill procedures.
Strong AWS fundamentals for data platforms, including S3, IAM, KMS, networking basics, and logging/auditing.
Experience implementing data governance and security controls in Databricks, such as Unity Catalog and permission management.
Demonstrated experience leading the use of approved AI-assisted software development tools while ensuring safety, performance, and security.

Save