Lead Software Engineer - Data Engineer, Python, AWS

Testing Site - JPMC; Plano (TX); On-site; USD 120,000 - 190,000; Full time

Job summary

JPMorgan Chase is seeking a Lead Software Engineer-Cloud Data for its Home Lending and Servicing team. You will design, build, and deploy scalable data pipelines on AWS using Spark and Python/Java, delivering secure and reliable data products in an agile environment.

The role emphasizes leadership, mentoring, and driving best practices in cloud data engineering while collaborating with cross-functional teams to achieve business outcomes.

Qualifications

• 5+ years of applied software engineering experience.
• Hands-on experience in system design, development, testing, and operational stability.
• Proficient in Java or Python, SQL, and at least one additional language (e.g. Scala) for data tasks.
• Hands-on experience utilizing Apache Spark for large-scale data processing and analytics.
• Experience with infrastructure automation tools such as AWS CloudFormation or Terraform.
• Proficiency across SDLC with emphasis on CI/CD, security, and resiliency.
• Experience with AWS data services such as Aurora, DynamoDB, S3, and RDS.
• AWS Certifications.

Responsibilities

• Executes creative software solutions, design, development, and debugging with ability to tackle complex problems.
• Develops secure high-quality production code and reviews peers' work.
• Architects scalable data pipelines and solutions on AWS (S3, Redshift, Glue, EMR, Lambda, Athena).
• Leads design reviews and evaluation sessions with internal/external teams.
• Mentors junior engineers and promotes best practices across the team.
• Drives CI/CD, security, and operational stability of cloud data systems.
• Maintains thorough documentation of architectures and processes.
• Stays current with AWS advancements and applies new capabilities.

Skills

Java

Python

Apache Spark

SQL

Scala

AWS

Terraform

CloudFormation

CI/CD

Data engineering

System design

Mentoring

Agile

Security

Tools

AWS S3

Amazon Redshift

AWS Glue

AWS EMR

AWS Lambda

Amazon Athena

DynamoDB

RDS

Aurora

Terraform

CloudFormation

Snowflake

Databricks

Apache Spark

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-Cloud Data/Python/Java/Spark at JPMorgan Chase within the Consumer and Community Banking's Home Lending and Servicing team, youwill play a crucial role in an agile team dedicated to enhancing, building, and delivering reliable, market-leading technology products that are secure, stable and scalable.

Job responsibilities

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Develops secure 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
• Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
• Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
• Adds to team culture of diversity, opportunity, inclusion, and respect
• Architect, develop, and deploy scalable data pipelines and solutions on AWS using services such as S3, Redshift, Glue, EMR, Lambda, and Athena
• Create and optimize data models, build robust ETL processes, and ensure efficient ingestation, transformation, and storage
• Monitor, troubleshoot, and tune data pipelines and cloud resources for optimal performance, reliability, and cost efficiency
• Maintain comprehensive documentation of data architectures, processes and best practices; mentor junior engineers and share knowledge within the team
• Stay current with AWS advancements, evaluate new services and tools, and drive continuous improvement in cloud data engineering practices

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Hands-on professional experience in one or more programming language(s), including Java or Python, proficiency in Python, SQL, and at least one additional language (e.g. Java or Scala) for data engineering tasks
• Hands-on experience utilizing Apache Spark for large-scale data processing, including developing and optimizing data pipelines, performing real-time and batch analytics, and leveraging Spark’s libraries for machine learning and data transformation to drive actionable business insights.
• Experience with infrastructure automation tools such as AWS CloudFormation or Terraform
• Proficiency in all aspects of the Software Development Life Cycle
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• Demonstrated experience in system design, including architecting scalable and reliable solutions, selecting appropriate technologies, defining system components and their interactions, and ensuring alignment with business requirements and performance goals through detailed documentation and collaborative design reviews.
• Experience with AWS services related to data storage and management, such as AWS Aurora, DynamoDB, S3, and RDS
• Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
• AWS Certifications

Preferred qualifications, capabilities, and skills

• Extensive experience working with relational databases such as Oracle, MySQL, and SQL Server, including designing schemas, writing complex queries, optimizing performance, and ensuring data integrity for a variety of business applications.
• Snowflake experience is a plus
• Databricks experience is a plus