Lead Software Engineer

JPMorgan Chase

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Jersey City, NJ
Employment: Full-time
Posted: 107 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $197k

$129k $246k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $167,500–$226,350.

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 1227 open roles on FindRole.

Listed pay typically runs $144,716–$200,000 across 12 roles with salary data.

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At a glance

TL;DR · Lead Software Engineer

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As a Lead Software Engineer - Databricks within Corporate Technology, you will join an agile team to build and deliver secure, scalable data collection, storage, and analytics solutions. You will maintain critical data pipelines and architectures across various business functions to support firm objectives. Your daily responsibilities include architecting a Databricks Lakehouse on AWS, designing bronze, silver, and gold layers, and implementing resilient batch and streaming ingestion from AWS sources. You will utilize Spark, Delta Lake, Delta Live Tables, and Unity Catalog while managing S3, IAM, and KMS. You must ensure operational excellence through monitoring, incident response, and cost management. Key skills include Terraform for Infrastructure as Code, CI/CD, and mentoring engineers in Spark best practices to solve complex data governance and performance challenges.

Skills

Databricks AWS Spark Delta Lake Terraform S3 Unity Catalog Delta Live Tables Structured Streaming CI/CD IaC CDC VPC IAM KMS Data Governance Monitoring Testing

What you'll do

Architect and design multi-layer data products within a Databricks Lakehouse hosted on AWS.
Build and operate resilient batch and streaming data pipelines using Spark and Delta Lake.
Implement data governance, security controls, and PII classification using Unity Catalog and IAM.
Productionize workloads using Databricks Workflows with robust retries, checkpointing, and idempotency.
Optimize Spark performance, cluster sizing, and storage layouts to manage costs and processing speed.
Lead engineering standards by conducting design reviews, code reviews, and mentoring junior engineers.
Deploy infrastructure and pipelines using Terraform for CI/CD and Infrastructure as Code.
Manage operational reliability through monitoring, incident response, and SLO/SLA management.

What we're looking for

7+ years of experience in data engineering.
2+ years of experience leading delivery or architecture for multi-team data platforms.
Hands-on experience building and operating a Databricks Lakehouse hosted in AWS.
Deep experience with Delta Lake, Spark on Databricks, and streaming/batch pipelines.
Strong AWS fundamentals including S3, IAM, KMS, and networking basics.
Experience implementing data governance, security controls, and CI/CD using Terraform.
Proven ability to lead, mentor, and set engineering standards for Spark and Databricks best practices.
Experience with monitoring, incident response, and managing SLO/SLA requirements.

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