Data Engineer- AWS/PySpark/ETL

JPMorgan Chase & Co.•Columbus, OH

About The Position

As a Data Engineer II at JPMorgan Chase within the Consumer and Community Banking and Data Technology, you serve as a seasoned member of an agile team to design and deliver trusted data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Requirements

Formal training or certification on data engineering concepts and 2+ years applied experience
Experience with ETL tools like Ab Initio, Informatica, Data Pipeline and workflow management tools (Airflow, etc.)
Strong hands on coding experience with PySpark, Python and AWS
Experience working with modern Data Lakes : (Snowflake, Databricks etc.)
Hands-on practical experience delivering system design, application development, testing, and operational stability
Very strong problem solving skills
Proficiency in automation and continuous delivery methods

Nice To Haves

Advanced in one or more programming language(s) like SQL, Java etc
Proficient in all aspects of the Software Development Life Cycle
Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning etc.)
In-depth knowledge of the financial services industry and their IT systems
Practical cloud native experience
Proven leadership and mentoring experience with varying levels of software engineers

Responsibilities

Develops secure high-quality production code, and reviews and debugs code written by others
Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
Collaborate closely with cross-functional teams to develop efficient data pipelines to support various data-driven initiatives
Implement best practices for data engineering, ensuring data quality, reliability, and performance
Contribute to data modernization efforts by leveraging cloud solutions and optimizing data processing workflows
Perform data extraction and implement complex data transformation logic to meet business requirements
Leverage advanced analytical skills to improve data pipelines and ensure data delivery is consistent across projects
Monitor and executes data quality checks to proactively identify and address anomalies
Ensure data availability and accuracy for analytical purposes
Communicate technical concepts to both technical and non-technical stakeholders