Backend Python Databricks Software Engineer III

JPMorgan Chase

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Quick summary

Work type: On-site
Location: Plano, TX
Employment: Full-time
Posted: 4 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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How this pay compares to similar roles

Similar $185k

$133k most similar roles pay here $234k

This listing doesn't post a salary. Most similar roles pay $154,950–$214,125.

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 1174 open roles on FindRole.

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At a glance

TL;DR · Backend Python Databricks Software Engineer III

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As a Backend Python/Databricks Software Engineer III on the Consumer & Community Banking Finance Data Engineering team, you will design, build, and maintain scalable backend data engineering solutions to power critical financial reporting and analytics. You will develop high-quality production code, create PySpark-based data processing pipelines, and deploy scalable modules on Databricks while ensuring alignment with platform architecture standards. Your daily work involves troubleshooting complex technical problems, producing architecture artifacts, and translating finance business requirements into technical solutions. You will utilize Python, PySpark, and enterprise-authorized AI coding assistant tools to improve code quality and delivery speed. The role requires expertise in the Software Development Life Cycle, including CI/CD and application resiliency. You will manage large, diverse financial datasets to solve complex data challenges within a highly regulated financial services environment.

Skills

Python PySpark Databricks Apache Spark AWS S3 Glue Lambda Kafka Terraform Apache Airflow CI/CD Agile System Design Data Engineering

What you'll do

Design, build, and maintain scalable backend data engineering solutions for critical financial reporting.
Develop high-quality production code using Python and PySpark for large-scale data processing.
Build, deploy, and support scalable data engineering modules on the Databricks platform.
Utilize AI coding tools to generate, refactor, and document code while ensuring security standards.
Create architecture and design artifacts for complex applications while ensuring technical constraints are met.
Analyze large financial datasets to develop visualizations and reporting for system improvements.
Identify hidden patterns in data to improve coding hygiene and overall system architecture.
Translate business requirements from product managers into scalable technical solutions.

What we're looking for

Formal training or certification on software engineering concepts and 3+ years of applied experience.
Hands-on practical experience in system design, application development, testing, and operational stability.
Experience developing, debugging, and maintaining code in a large corporate environment using modern programming and database querying languages.
Proficiency in Python backend development with hands-on experience building and optimizing PySpark data pipelines in production environments.
Demonstrated experience with Databricks, including module development, deployment, and ongoing operational support.
Hands-on experience using enterprise-authorized AI-assisted software development tools while ensuring output correctness, performance, and security.
Understanding of the Software Development Life Cycle, agile methodologies (CI/CD), application resiliency, and security.
Experience with Apache Spark, Kafka, AWS services, infrastructure-as-code, or financial data governance (preferred).

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