Data Software Engineer II - PySpark/ETL/AWS/

JPMorgan Chase & Co.•Jersey City, NJ

17h

About The Position

As a Software Engineer II at JPMorganChase within the Consumer and Community Banking Data 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.

Requirements

Formal training or certification on software engineering concepts and 2+ years applied experience
Experience with ETL tools such as Ab Initio, Informatica, and Data Pipeline, as well as workflow orchestration tools (e.g., Airflow)
Strong hands-on development experience with PySpark, Python, and AWS
Experience working with modern data lake platforms (e.g., Snowflake, Databricks)
Proven, hands-on experience across system design, application development, testing, and ensuring operational stability
Hands-on practical experience in system design, application development, testing, and operational stability
Proficiency with automation and continuous delivery (CI/CD) practices and methods
Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
Demonstrable ability to code in one or more languages
Experience across the whole Software Development Life Cycle
Emerging knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)

Nice To Haves

In-depth knowledge of the financial services industry and their IT systems
Practical cloud native experience

Responsibilities

Executes standard software solutions, design, development, and technical troubleshooting
Develop secure, high-quality production code; review, debug, and improve code written by other engineers.
Applies knowledge of tools within the Software Development Life Cycle toolchain to improve the value realized by automation
Applies technical troubleshooting to break down solutions and solve technical problems of basic complexity
Adds to team culture of diversity, opportunity, inclusion, and respect
Identify recurring issues and implement automation or permanent fixes to reduce remediation effort and improve application/system stability.
Partner with cross-functional teams to design and deliver efficient data pipelines supporting data-driven initiatives.
Apply data engineering best practices to ensure data quality, reliability, scalability, and performance
Contribute to data modernization by leveraging cloud capabilities and optimizing data processing workflows.
Perform data extraction and implement complex transformation logic to meet business and reporting requirements and use advanced analytical skills to continuously enhance pipeline efficiency and ensure consistent data delivery across projects.
Monitor pipelines and execute data quality checks to proactively detect, investigate, and resolve data anomalies. and ensure timely data availability and high accuracy to support analytics and decision-making needs.