Lead Software Engineer

JPMorgan Chase

Confirmed live yesterday Trusted

Quick summary

Work type: On-site
Location: Wilmington, DE
Posted: 65 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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How this pay compares to similar roles

Similar $202k

$182k 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.

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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.

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At a glance

TL;DR · Lead Software Engineer

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Lead Software Engineer - Databricks joins the Corporate Sector’s Enterprise Technology team to build and deliver secure, scalable technology products. As a core technical contributor, you will architect and deliver high-throughput, low-latency data pipelines on Databricks using Apache Spark, Delta Lake, and Unity Catalog. Your daily responsibilities include managing cluster strategies, orchestrating workflows with AWS services, designing ingestion frameworks, and performing deep Spark performance tuning to optimize cost and throughput. You will develop reusable libraries in Python or Java while implementing CI/CD via Git and Terraform. The role requires expertise in SQL modeling, ETL/ELT pipeline construction, and the integration of enterprise-authorized AI-assisted engineering practices. You will solve complex data engineering challenges by ensuring high data quality, lineage, and governance within a robust Lakehouse architecture to support various business functions.

Skills

Databricks Apache Spark Delta Lake Python Java SQL AWS Terraform Airflow Unity Catalog CI/CD Git ETL ELT Data Modeling Streamlit React Structured Streaming

What you'll do

Architect and deliver high-throughput, low-latency data pipelines using Databricks and Apache Spark.
Manage Databricks cluster strategies including runtime selection, autoscaling, and performance tuning.
Establish Lakehouse patterns using Delta Lake to ensure scalable and maintainable data platforms.
Automate data pipelines and jobs using Databricks Workflows and AWS orchestration services.
Design secure ingestion and transformation frameworks with integrated data quality and governance via Unity Catalog.
Develop reusable libraries, frameworks, and APIs in Python or Java with comprehensive test coverage.
Implement CI/CD pipelines using Git workflows and Terraform for infrastructure deployment.
Lead the adoption of enterprise-authorized AI-assisted engineering practices to improve code quality and delivery speed.

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 or AWS EMR.
Advanced hands-on expertise in Databricks features including Delta Lake, Unity Catalog, Workflows, Repos, SQL Warehouses, and cluster optimization.
Proven ability to architect and operate reliable batch and streaming ETL/ELT data pipelines with schema design and reliability engineering.
Deep Spark performance tuning skills to diagnose bottlenecks and optimize 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 while ensuring security and validation standards.

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