Senior Manager of Software Engineering, Reference Data Engineering

JPMorgan Chase

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Quick summary

Work type
On-site
Location
Chicago, IL
Posted
3 days ago
Freshness
Confirmed live today

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How this pay compares to similar roles

Similar $184k
$110k most similar roles pay here $248k

This listing doesn't post a salary. Most similar roles pay $158,956–$209,000.

Based on 240 similar postings.

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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 1138 open roles on FindRole.

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At a glance

TL;DR · Senior Manager of Software Engineering, Reference Data Engineering

As a Senior Manager of Software Engineering - Reference Data Engineering within the Corporate Sector's Reference Data Engineering team, you will provide technical coaching, oversight, and direction to a team of engineers. You will manage the end-to-end lifecycle of features while scaling operating practices for AI-assisted engineering and SDLC automation. The role involves designing and developing Java and Spring Boot microservices to deliver real-time data products within a modern data mesh architecture. You will solve complex data infrastructure challenges by building intelligent, self-healing platforms using technologies including AWS (EC2, S3, Lambda), Databricks, Snowflake, Kafka, Kinesis, Spark Structured Streaming, and MongoDB. Your work focuses on the technical challenge of providing high-performance, multi-tenant data delivery and automated reconciliation for financial infrastructure while ensuring system reliability through robust testing and proactive technical debt remediation.

What does a Software Engineering Manager earn?

Median $224375 from 112 postings across 41 companies.

See salary data

What you'll do

  • Provide technical coaching, oversight, and direction for a team of entry-level to mid-level software engineers.
  • Scale operating practices for AI-assisted engineering and SDLC automation across multiple teams to improve delivery speed and quality.
  • Design and develop Java/Spring Boot microservices for real-time data product delivery and platform capabilities.
  • Own features end-to-end, including requirements, system design, implementation, testing, deployment, and monitoring.
  • Optimize performance, scalability, and cost efficiency of microservices and data pipelines while ensuring high data integrity.
  • Identify and remediate technical debt while maintaining high engineering standards through code reviews and debugging.
  • Manage large-scale data infrastructure using AWS, Databricks, and event-driven streaming technologies like Kafka and Kinesis.
  • Contribute to production support, incident response, and the creation of technical documentation and runbooks.

What we're looking for

  • Formal training or certification on software engineering concepts and 5+ years of applied experience.
  • At least 2 years of experience leading technologists to manage and solve complex technical items within a domain of expertise.
  • Experience leading multi-team adoption of enterprise-authorized AI-assisted development tools, including defining governance and measuring outcomes.
  • Expert-level Java proficiency with deep knowledge of Spring Boot, Spring Cloud, Spring Data, and Spring Security.
  • Production-level experience with AWS services (EC2, S3, Lambda, etc.) and databases including NoSQL, Snowflake, and Databricks.
  • Proficiency in building event-driven microservices using Kafka, Kinesis, or Spark Structured Streaming.
  • Experience with version control, CI/CD pipelines, and modern DevOps practices like Docker, Kubernetes, and Terraform.
  • Python experience with data engineering, AWS certifications, and familiarity with data mesh patterns (preferred).

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