Software Engineer [Multiple Positions Available]

JPMorganChase•Jersey City, WA

8d•Onsite

About The Position

We are seeking Software Engineers to design, develop, and maintain scalable and efficient software solutions. This role involves writing clean, maintainable code, building and optimizing data pipelines for analytics and machine learning, and designing robust, scalable, and cost-effective system architectures. You will analyze existing codebases, redesign for modern cloud-based architecture, and identify/resolve performance bottlenecks. Collaboration with cross-functional teams, mentorship of junior engineers, and implementation of testing strategies are key aspects of this position. Ensuring compliance with security and privacy best practices, maintaining CI/CD pipelines, and diagnosing/resolving technical issues are also core responsibilities.

Requirements

Master's degree in Information systems, Computer Engineering, Computer Science, or related field of study plus 2 years of experience in the job offered or as Software Engineer, Data Engineer, or a related occupation.
Bachelor's degree in Information systems, Computer Engineering, Computer Science, or related field of study plus 4 years of experience in the job offered or as Software Engineer, Data Engineer, or a related occupation.
Performing data manipulation, data structuring, data design flows, and query optimization using SQL to utilize Common Table Expressions (CTE) window functions, Dynamic SQL and Python.
Utilizing multithreading, multiprocessing and distributed computing to process data sets using PySpark and Python.
Using AWS services to build and manage cloud-based applications and maintaining AWS resources including EC2, S3, Lambda, RDS, EKS, ECS, SQS and SNS.
Developing software in a microservices environment deploying REST API using AWS Lambda, Step Functions, and API Gateway, for serverless architecture.
Building applications that utilize JSON and XML formatted data files and service payloads for data transfers.
Developing and automating data pipelines using Python and Spark to improve product experience.
Building scalable Spark data pipelines and leveraging the scheduler and executor frameworks.
Designing and developing financial models and financial workflows using Python.
Designing and developing asynchronous event-driven services using AWS services, SNS, and SQS.
Designing and developing automated unit and integration testing cases for Python and PySpark based data pipelines.
Working with NoSQL databases to manage unstructured data for storing user activity and producing reports.
Utilizing Python frameworks to build webservices and REST (Representational State Transfer) API's.
Building CI/CD pipelines for large-scale applications.
Utilizing Security protocols including OAuth and applying them to both services and consumption.
Using Terraform for implementing infrastructure as code for large-scale applications on AWS.
Developing and maintaining dynamic and interactive dashboards using Tableau leveraging advanced visualization, ETL automation, and ODBC connectors.

Responsibilities

Design, develop, and maintain scalable and efficient software solutions including writing clean, maintainable, and well-documented code.
Build and optimize data pipelines including data ingestion, transformation, and processing to support analytics and machine learning tasks.
Design system architecture that is robust, scalable, and cost-effective involving making decisions about the best technologies and practices to analyze existing code bases and redesign for modern cloud-based architecture.
Identify and resolve performance bottlenecks applications and data processing workflows to ensure high efficiency and speed.
Work closely with cross-functional teams, including data scientists, product managers, and other engineers.
Provide mentorship and guidance to junior engineers.
Implement testing strategies to ensure the reliability and quality of software solutions including writing unit tests, integration tests, and conducting code reviews.
Ensure applications and data processing workflows comply.
Implement best practices for data security and privacy.
Maintain CI/CD pipelines to automate the deployment process and ensure smooth and rapid delivery of software updates.
Diagnose and resolve technical issues in a timely manner to minimize downtime and ensure smooth operation of applications and services.