Lead Software Engineer - Big Data(Data Engineer), Python, and AWS

JP Morgan Chase; Plano (TX); On-site; USD 180,000 - 280,000; Full time

Job summary

JPMorganChase in Plano, Texas, seeks a Lead Software Engineer within CIB to advance data platform products, build scalable pipelines, and deliver secure, reliable data services across the enterprise.

You will contribute as a core technical developer, applying AI-assisted methods, designing data architectures, and ensuring compliance while collaborating with cross-functional teams on complex data workflows.

Expert in Spark, Python, AWS, and Databricks preferred.

Qualifications

• Formal training or certification on data engineering concepts and 5+ years applied experience.

Responsibilities

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems.
• Delivers data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way.
• Uses enterprise-authorized AI capabilities within the work environment to accelerate data products and model design analysis and documentation, validating outputs and handling data according to sensitivity and security requirements.
• Evaluates and reports on access control processes to determine effectiveness of data asset security with minimal supervision.
• Applies reuse-first, AI-assisted practices within delivery and operational routines (e.g., backup/recovery validation and access control review support), ensuring traceability/auditability and alignment to resiliency and security expectations.
• Develops secure and high-quality production code, and reviews and debugs code written by others.
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems

Skills

Big Data

Apache Spark

Python

Data engineering

CI/CD

Security

NoSQL databases

Relational databases

Iceberg tables

AI capabilities usage

Tools

Databricks

Snowflake

AWS cloud

Terraform

APIs

Job description

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorganChase within the CIB, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology data products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for maintaining critical data pipelines and architectures across multiple technical areas within various business functions in support of the firm's business objectives.

Job responsibilities

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
• Delivers data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way
• Uses enterprise-authorized AI capabilities within the work environment to accelerate data products and model design analysis and documentation, validating outputs and handling data according to sensitivity and security requirements.
• Evaluates and reports on access control processes to determine effectiveness of data asset security with minimal supervision
• Applies reuse-first, AI-assisted practices within delivery and operational routines (e.g., backup/recovery validation and access control review support), ensuring traceability/auditability and alignment to resiliency and security expectations.
• Develops secure and high-quality production code, and reviews and debugs code written by others
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems

Required qualifications, capabilities, and skills

• Formal training or certification on data engineering concepts and 5+ years applied experience
• Proficient at processing and analyzing large datasets using Big Data technologies, including Apache Spark, across data platforms comprising of Redshift, SQL DB, RDS and Databricks.
• Design, development, and implementation of scalable data pipelines and data matching solutions on AWS, utilizing Python for data engineering tasks.
• Strong experience in setup and configuration of services such as S3, Step Functions, EMR, Glue, Lambda, RDS, EventBridge, Step-Functions and API Gateway for scripting, automation, and orchestration of data workflows.
• Strong hands-on experience with Databricks and distributed data processing technologies.
• Understanding of data architecture, data modeling, data integration, and data product principles.
• Experience designing and operating large-scale data platforms and data products in complex enterprise environments.
• Development of semantic layer for data consumption using Iceberg tables and APIs.
• Implementation of continuous deployment and integration processes using Infrastructure as Code tools, including Terraform.
• Troubleshoot and resolve issues related to application code and data workflows.
• Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support data engineering workflows with strong validation habits and awareness of data sensitivity.
• Working experience with both relational and NoSQL databases
• Advanced in one or more programming language(s)
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security

Preferred qualifications, capabilities, and skills

• Experience working with modern enterprise data platforms and cloud-native data architectures.
• Experience supporting real-time, analytical, or AI/ML-oriented data use cases.
• Databricks, Snowflake, AWS cloud, or Data Engineering certifications