Lead Software Engineer - AWS

Job summary: As a Manager of Software Engineer at JPMorgan Chase within our Workforce Technology team, you are part of an agile team that works to enhance, design, and deliver the software components of the firm’s state-of-the-art technology products in a secure, stable, and scalable way. As an emerging member of a software engineering team, you execute software solutions through the design, development, and technical troubleshooting of multiple components within a technical product, application, or system, while gaining the skills and experience needed to grow within your role. Job responsibilities : Manage data integration and data analysis of disparate systems Build extensible data acquisition and integration solutions to meet the functional and non-functional requirements of the client Implement processes and logic to extract, transform, and distribute data across one or more data stores from a wide variety of sources 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 Provide problem-solving expertise and complex analysis of data to develop business intelligence integration designs Interface with other internal product development teams as well as cross functional teams (Product Management, Integration Engineering, Quality Engineering, System Admin Teams) Working with remote and geographically distributed teams to enable building the right products, using the right building blocks, and making them consumable by other products easily Required qualifications, capabilities, and skills: Experience in data integration projects using Big Data Technologies, preferably related to human resources analytics Experience in managing team of at least 5-10 engineers. Experience in AWS Data Warehousing and database platforms with hands-on delivery using EMR, S3, AWS Glue, Lambda, Apache Airflow and Infrastructure as Code (IaC) (e.g., Terraform/CloudFormation) Hands-on experience on Spark engineering with PySpark/Scala for building and optimizing scalable data pipelines and 2+ years hands-on experience building streaming applications using Kafka 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 Strong experience in CICD using Jenkins, Git, Artifactory, Yaml, Maven for Cloud deployments Good knowledge of Big Data querying tools, such as Athena, RDS, Databricks Experience in integrating data from different types of file-storage formats like Parquet, ORC, Avro and table formats like Delta Lake or Iceberg Good knowledge of Java opensource, API standards, JUnits, Spring Boot applications, Swagger Setup Experience using AI-assisted developer productivity tools (e.g., GitHub Copilot) to speed up development, testing, and remediation Strong technical understanding in building scalable, high performance distributed services/systems Strong knowledge of Data Warehousing, Data Modeling and Data Lake, Data Security concepts Possesses strong problem solving, troubleshooting, and analytical skills, as well as excellent communication, presentation and interpersonal, including the ability to communicate complex concepts clearly to different audiences Experience in technologies like Oracle/SQL and NoSQL data stores such as DynamoDB Ability to quickly learn new technologies in a dynamic environment Preferred qualifications: Experience in Databricks, Experience in Human Resources analytics