This is your chance to change the path of your career and guide multiple teams to success at one of the world's leading financial institutions.

As a Manager of Software Engineering at JPMorgan Chase within the Consumer and Community Banking - Data Tech space, you lead multiple teams and manage day-to-day implementation activities by identifying and escalating issues and ensuring your team’s work adheres to compliance standards, business requirements, and tactical best practices.

Job responsibilities

Provides guidance to immediate team of software engineers on daily tasks and activitiesSets the overall guidance and expectations for team output, practices, and collaborationAnticipates dependencies with other teams to deliver products and applications in line with business requirementsManages stakeholder relationships and the team’s work in accordance with compliance standards, service level agreements, and business requirementsCreates a culture of diversity, equity, inclusion, and respect for the team members and prioritizes diverse representation

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and 5+ years applied experience. In addition, demonstrated coaching and mentoring experience.Experience leading technology projects and Experience managing technologists.Minimum 8 yrs proven experience in full-stack software development, using Java, Spring based technologies in AWS / Cloud environment.Demonstrable success in leading and managing software engineering teams, with a focus on individual growth and overall team performance.Proven experience with Apache Spark (batch and streaming) for large-scale data processing. Proven experience and strong knowledge of AWS services including S3, EC2, EMR, ECS, Lambda, Glue, Aurora DB, SQS , SNS, Step function, API Gateway.Expertise in Databricks and Snowflake for collaborative data engineering and analytics. Experience in Apace Iceberg for large scale analytics on Data lake.Experience with Terraform for provisioning, securing, and managing cloud infrastructure for data workloads. Good knowledge of data governance, access controls, data lineage, and compliance standards for implementing secure data pipelines and handling sensitive information responsibly.Proficiency in tuning Spark jobs, optimizing SQL queries on Snowflake, and troubleshooting distributed systems.

Preferred qualifications, capabilities, and skills

Experience with CI/CD pipelines for automated deployment. Implementing automated testing strategies including Unit , Contract, integrations, and end to end tests. Knowledge in building scalable RESTful APIs using Spring Boot.Experience with PySpark for developing Spark-based data pipelines using Python.Experience integrating AI agents or automation frameworks to optimize data engineering tasks.