Lead Software Engineer

JPMorgan Chase

Confirmed live today Trusted

Quick summary

Work type
On-site
Location
Plano, TX
Employment
Full-time
Posted
54 days ago
Freshness
Confirmed live today

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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 $167,612–$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 1226 open roles on FindRole.

Listed pay typically runs $156,750–$215,000 across 5 roles with salary data.

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At a glance

TL;DR · Lead Software Engineer

As a Lead Software Engineer - Databricks within the Corporate Technology team, you will join an agile team to build and deliver trusted, scalable technology products. You will lead the architecture and delivery of high-throughput, low-latency data pipelines using Databricks and Apache Spark. Your daily responsibilities include establishing Lakehouse patterns with Delta Lake, managing cluster strategies, and orchestrating automated workflows. You will design secure ingestion frameworks, enforce data governance using Unity Catalog, and perform deep Spark performance tuning. The role requires proficiency in Python, Java, and SQL to build reusable libraries and APIs. You will implement CI/CD pipelines using Git and Terraform while championing AI-assisted engineering practices. This position solves complex data engineering problems by ensuring reliable ETL/ELT processing, data quality, and secure infrastructure management.

What you'll do

  • Lead the architecture and delivery of high-throughput, low-latency data pipelines using Databricks and Apache Spark.
  • Establish and evolve Lakehouse patterns with Delta Lake to ensure performant and maintainable data platforms.
  • Own Databricks cluster strategy, including runtime selection, autoscaling, and Spark configuration.
  • Orchestrate and automate data pipelines using Databricks Workflows and AWS eventing services.
  • Design secure ingestion and transformation frameworks to produce trusted and refined datasets.
  • Enforce data quality, lineage, and governance using Unity Catalog and AWS Glue Catalog.
  • Perform Spark performance engineering and tuning to optimize job costs and throughput.
  • Build and maintain reusable libraries and APIs in Python or Java with comprehensive test coverage.

What we're looking for

  • Formal training or certification on software engineering concepts and 5+ years of applied experience.
  • Advanced experience in software engineering and data engineering with production delivery using Apache Spark on Databricks and/or AWS EMR.
  • Advanced hands-on Databricks expertise across Delta Lake, Unity Catalog, Workflows, Repos/notebooks, and SQL Warehouses.
  • Proven ability to architect and operate reliable ETL/ELT data pipelines for batch and streaming with schema design and reliability engineering.
  • Deep Spark performance tuning skills to diagnose bottlenecks and optimize jobs for scalability, cost, and runtime efficiency.
  • Strong programming proficiency in Python and/or Java for data processing, platform tooling, and automation.
  • Strong SQL and analytics data modeling expertise, including dimensional/star schema design and Lakehouse best practices.
  • Demonstrated experience leading the use of approved AI-assisted software development tools and coaching teams on responsible AI security.

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