Full-Time

AWS Lead Software Engineer-Python/PySpark

JP Morgan Chase

JP Morgan Chase

10,001+ employees

Global financial services with diversified offerings

No salary listed

Wilmington, DE, USA

In Person

On-site in Wilmington, Delaware.

Category
DevOps & Infrastructure (1)
Software Engineering (1)
Required Skills
DynamoDB
Microsoft Azure
Redshift
Python
Airflow
Software Testing
BigQuery
Apache Spark
SQL
AWS
Terraform
Snowflake
Google Cloud Platform

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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
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
  • 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.
Desired Qualifications
  • 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

A global financial services firm offering investment banking, asset management, private equity, financial services, and consumer banking to individuals and institutions. It works by providing advisory, lending, trading, and financing services through a worldwide network, earning revenue from interest, fees, and trading commissions, and using its data and the JPMorgan Chase Institute to analyze economies. It stands apart from peers due to its size, full-range services across consumer and corporate markets, extensive market access, and in-house data-driven insights. Its goal is to deliver comprehensive financial products with integrity and growth while supporting clients and communities through data-backed analysis and targeted programs.

Company Size

10,001+

Company Stage

IPO

Headquarters

New York City, New York

Founded

1959

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Simplify Jobs

Simplify's Take

What believers are saying

  • JPMorgan earned $21.2 billion in Q2 2025, leading five major US banks in profit.
  • AI automates multistep workflows targeting $2 billion in annual savings by 2025.
  • Revenue surged 27% to $58 billion in Q2 2026, beating analyst estimates by 13%.

What critics are saying

  • New DOJ emails trigger Senate scrutiny over Dimon's knowledge of Epstein's 1998-2013 client status.
  • Epstein victims may reopen liability lawsuits despite prior $290 million and $75 million settlements in 2023.
  • Governance failures linked to Epstein ties could trigger regulatory penalties and negative media cycles within 12-18 months.

What makes JP Morgan Chase unique

  • Proprietary LLM Suite deployed to 230,000 employees drives 30-40% efficiency gains.
  • OmniAI platform enables real-time fraud detection saving nearly $1.5 billion cumulatively.
  • Ranked first on Evident AI Index for banking AI maturity for four consecutive years.

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Benefits

Health Insurance

Flexible Work Hours

Paid Sick Leave

Paid Holidays

Growth & Insights and Company News

Headcount

6 month growth

-5%

1 year growth

-5%

2 year growth

-5%
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