AWS Lead Software Engineer-Python/PySpark

JPMorgan Chase & Co.
Wilmington, United States of America
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Wilmington, United States of America

Tech stack

Artificial Intelligence
Airflow
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Software Applications
Automation of Tests
Unit Testing
Azure
Google BigQuery
Cloud Computing
Software Quality
Code Review
Computer Programming
Continuous Delivery
Continuous Integration
Data Governance
Data Infrastructure
ETL
Data Systems
Distributed Computing Environment
Amazon DynamoDB
Hive
Identity and Access Management
Python
Performance Tuning
Systems Development Life Cycle
Query Optimization
Software Tools
Cloud Services
Standard Sql
Secure Coding
Software Engineering
Software Systems
SQL Databases
Data Streaming
Strategies of Testing
Toolchain
Workflow Management Systems
Data Processing
Google Cloud Platform
Snowflake
Spark
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Containerization
Data Lake
PySpark
Kubernetes
Apache Flink
Production Code
Kafka
Spark Streaming
Front End Software Development
Functional Programming
Cloudwatch
Api Gateway
Amazon Web Services (AWS)
Terraform
Code Restructuring
Docker
Redshift

Job description

  • 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
  • Design reusable data processing and data quality frameworks, writing production-ready Python/PySpark with testing, performance tuning, and maintainable patterns
  • Build and continuously improve reliable batch and streaming data pipelines, enhancing scalability, security, and operational excellence for critical data systems
  • Develop data models and transformations using SQL and dbt to support analytics, BI, and reporting use cases
  • Create and operate workflow orchestration (e.g., Airflow) to schedule, monitor, and troubleshoot data jobs, leveraging infrastructure-as-code (e.g., Terraform) to provision and manage platform infrastructure
  • Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.

Requirements

  • Formal training or certification on software engineering concepts and 5+ years applied experience
  • Hands-on experience delivering end-to-end software solutions across system design, application development, testing, and operational stability; proficient in all aspects of the SDLC
  • Advanced programming skills, with strong Python expertise (including unit and integration testing) and advanced PySpark for building and maintaining data processing solutions
  • Proficiency with automation, CI/CD, and continuous delivery practices
  • Hands-on experience building and operating cloud-native solutions on AWS (e.g., EKS/ECS, Lambda, API Gateway, VPC, IAM, S3, RDS/DynamoDB, SQS/SNS, CloudWatch/CloudTrail)
  • Experience building and running cloud data platforms on AWS, Google Cloud, or Azure
  • Experience with large-scale distributed data processing, performance tuning, and optimization
  • Strong SQL/Spark SQL skills, including data modeling, query optimization, and execution plan analysis
  • Experience with modern warehouse/lakehouse ecosystems (e.g., Redshift, BigQuery, Snowflake; Spark/Flink/Trino; Iceberg/Hudi) and using approved AI-assisted development tools with standards to validate correctness, performance, and security
  • Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices

Preferred qualifications, capabilities, and skills

  • Experience in financial services, ideally supporting home lending products and processes
  • Familiarity with modern front-end technologies and patterns for building user-facing experiences
  • Strong data modeling experience for analytics and reporting use cases
  • Knowledge of data platform security, risk, compliance, and governance practices
  • Experience building delivery automation for data/platform services, including CI/CD and containerized deployments (Docker, Kubernetes)
  • Expertise in modern data/streaming platforms and patterns (Kafka topic design and operations; Spark Structured Streaming and streaming ETL)
  • Ability to coach and mentor teammates, contribute to a collaborative and inclusive culture, and use AI-assisted engineering tools in an enterprise-safe way (spec-driven work, refactoring, code review); plus experience with Delta Lake and how it compares to Iceberg

Benefits & conditions

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.

About the company

As an AWS Lead Software Engineer-Python/PySpark at JPMorgan Chase within the Consumer and Community Banking Home Lending team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives., Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.

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