About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 436 open roles on FindRole.

Listed pay typically runs $152,000–$215,000 across 230 roles with salary data.

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At a glance

TL;DR · Lead Software Engineer, Java/Python, AWS, Spark

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The Lead Software Engineer role at JPMorganChase in Consumer and Community Banking involves leading an agile team to develop and maintain robust cloud-based data processing pipelines using Java or Python. This senior position requires expertise in distributed data frameworks like Apache Spark, AWS Data Lake services, and orchestration tools such as Airflow. The engineer will design scalable data models, ensure data integrity, and collaborate with cross-functional teams to implement innovative solutions that align with business objectives. Key responsibilities include driving data quality initiatives, managing end-to-end data infrastructure, and adhering to regulatory compliance standards while leveraging microservices architecture and serverless computing tools like Docker and Kubernetes.

Skills

Python Java Spark AWS Terraform Docker Kubernetes CI/CD Apache Airflow Snowflake SQL NoSQL JSON AVRO Parquet Microservices Serverless Test-Driven Development Behavior-Driven Development Infrastructure as Code Kafka Spinnaker

What you'll do

Lead the design and development of cloud-based data processing pipelines using AWS and Spark.
Refine large-scale data models for efficient storage and high-performance retrieval.
Translate complex business requirements into scalable data engineering solutions.
Champion innovation by identifying and implementing enhancements to data infrastructure.
Define and execute enterprise data strategy, managing end-to-end data infrastructure.
Ensure seamless data accessibility and strict compliance with data governance standards.
Align data engineering practices with business objectives for strategic relevance.

What we're looking for

Expertise in Java or Python and experience with Apache Spark for large-scale data processing.
Proficiency in cloud platforms like AWS and knowledge of distributed data Lakehouse services.
Hands-on experience with scheduling/orchestration tools such as Airflow and Kubernetes.
Strong skills in relational and NoSQL databases, including data serialization formats and big-data storage.
Experience in microservices architecture, serverless computing, and continuous integration/deployment practices.
Expertise in data modeling techniques and working with streaming platforms like Kafka.
Proficiency in Infrastructure as Code (IaC) tools such as Terraform or AWS CloudFormation.