Data Engineer II - AWS/PySpark/ETL
- LocationOH, United States
- Work typeNot stated
- EmploymentFull-time
- Posted4 November 2026
- SourceJPMorganChase's careers page (Oracle Recruiting)
Live checkFirst seen 4 days ago; still listed on JPMorganChase's careers page 3 days ago.
Moves fastWhen JPMorganChase takes a role down early, it is usually about 6 days after posting. Apply soon.
At a glance
- Skills and toolsAirflow, Spark, Python, AWS, SQL, Java, CI/CD, Machine learning
Read from the ad by RoleFinder, with rules and an AI reading; the description is the source.
About the role
Job Description
Be part of a dynamic team where your distinctive skills will contribute to a winning culture and team.
As a Data Engineer III at JPMorgan Chase within the CCB and Data Technology team, 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.
Job responsibilities
- 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
- Develops secure high-quality production code, and reviews and debugs code written by others
- 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
- 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
- Identify opportunities for process automation within data engineering workflows
- Communicate technical concepts to both technical and non-technical stakeho
Required qualifications, capabilities, and skills
- 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
- Willingness and ability to learn and pick up new skillsets
Preferred qualifications, capabilities, and skills
- 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
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