We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Software Engineer II at JPMorgan Chase within the Corporate Data Services, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities
 

Executes software solutions, design, development, and technical troubleshooting with the ability to think beyond routine or conventional approaches to build solutions or break down technical problems. Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems. Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development. Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems. Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture. Contributes to software engineering communities of practice and events that explore new and emerging technologies. Adds to team culture of diversity, equity, inclusion, and respect.
 

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and 3+ years of applied experience. Experience designing and implementing data pipelines in a cloud environment is required (e.g., Apache NiFi, Informatica). Strong experience in  migrating/developing data solutions in the AWS cloud is required, with experience needed in AWS Services and Apache Airflow. Building/implementing data pipelines using Databricks, such as Unity Catalog, Databricks Workflow, and Databricks Live Table. Solid understanding of agile methodologies such as CI/CD, application resiliency, and security.  Hands-on object-oriented programming experience using Python (especially PySpark) to write complex, highly optimized queries across large volumes of data. Knowledge or experience in big data technologies such as Hadoop/Spark, and in data modeling and ETL processing. Hands-on experience in data profiling and advanced PL/SQL procedures.

Preferred qualifications, capabilities, and skills

Familiarity with Oracle, ETL, and data warehousing, with cloud expertise being a plus. Exposure to cloud technologies.