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

JPMorgan Chase & Co. • Plano, TX

1d

About The Position

As a Lead Software Engineer within JPMorganChase’s Commercial & Investment Bank, you will contribute to an agile team building and enhancing secure, stable, and scalable technology data products. You will maintain critical data pipelines and architectures across technical areas and business functions, supporting the firm’s business objectives.

The role focuses on designing and delivering data collection, storage, access, and analytics solutions, including scalable AWS data pipelines and data-matching solutions using Python, Spark, Databricks, and related data technologies. You will develop secure production code, support data platform security and access-control reviews, and help improve operational stability and resiliency. The position also uses enterprise-authorized AI capabilities to support data engineering work, with attention to validation, data sensitivity, traceability, and security.

Requirements

• Formal training or certification in data engineering concepts and at least 5 years of applied experience.
• Proficiency processing and analyzing large datasets using Big Data technologies, including Apache Spark, across platforms such as Redshift, SQL databases, RDS, and Databricks.
• Experience designing, developing, and implementing scalable data pipelines and data-matching solutions on AWS using Python.
• Strong experience setting up and configuring AWS services, including S3, Step Functions, EMR, Glue, Lambda, RDS, EventBridge, and API Gateway, for workflow scripting, automation, and orchestration.
• 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.
• Experience developing semantic layers for data consumption using Iceberg tables and APIs.
• Experience implementing continuous deployment and integration processes using infrastructure-as-code tools, including Terraform.
• Experience troubleshooting and resolving application code and data workflow issues.
• Demonstrated experience using enterprise-authorized AI capabilities in data engineering workflows, with strong validation practices and awareness of data sensitivity.
• Working experience with relational and NoSQL databases.
• Advanced proficiency in one or more programming languages.
• Advanced understanding of agile methodologies and practices such as CI/CD, application resiliency, and security.

Nice To Haves

• 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.

Responsibilities

• Design, develop, and troubleshoot software solutions, including approaches to problems beyond routine or conventional methods.
• Deliver secure, stable, and scalable data collection, storage, access, and analytics platform solutions.
• Use enterprise-authorized AI capabilities to assist with data products, model design analysis, and documentation, validating outputs and following data sensitivity and security requirements.
• Evaluate and report on data asset access-control processes and their effectiveness.
• Apply reuse-first, AI-assisted practices to delivery and operational routines, including backup and recovery validation and access-control review support, while maintaining traceability and auditability.
• Develop secure, high-quality production code and review and debug code written by others.
• Identify opportunities to eliminate or automate recurring issue remediation to improve software and system operational stability.
• Design, develop, and implement scalable AWS data pipelines and data-matching solutions using Python.
• Set up and configure AWS services for scripting, automation, and orchestration of data workflows.
• Troubleshoot and resolve application code and data workflow issues.
• Implement continuous integration and deployment processes using infrastructure-as-code tools such as Terraform.
• Develop semantic layers for data consumption using Iceberg tables and APIs.

Benefits

• Competitive total rewards package, including base salary and, for eligible roles, commission-based pay and/or discretionary incentive compensation in cash and/or forfeitable equity.
• Comprehensive health care coverage.
• On-site health and wellness centers.
• Retirement savings plan.
• Backup childcare.
• Tuition reimbursement.
• Mental health support.
• Financial coaching.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed