Data Engineer III

This is your chance to change the path of your career and work at one of the world's leading financial institutions.

As a Python/Java Software Engineer III at JPMorgan Chase within the Consumer & Community Banking/Data Products team, 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.

• Demonstrate python development experience, including modular coding, creating reusable classes, logging, and testing
• Understand PySpark or distributed data processing frameworks
• Exhibit Proficiency in writing DBT macros, jinja templates, seeds, and custom test cases
• Have Experience with Airflow on MWAA, Astronomer or Kubernetes
• Show Proficiency with Glue jobs, Athena, Cloud watch, and Lambda
• Working knowledge of Terraform for infrastructure automation
• Apply Understanding of Iceberg, Hudi or Delta Lake and their role in data-lake architecture.
• Possess Ability to query and manage open-table format datasets.
• Designing and optimizing ETL/ELT pipelines.
• Demonstrate Knowledge of snowflake streams, tasks, roles, and warehouses.
• Utilize Experience with version control like GIT, testing frameworks, and code reviews

• Formal training or certification on software engineering concepts and 3+ years of applied experience
• Proficiency in Python/Java technology
• Hands-on practical experience in system design, application development, testing, and operational stability
• Proficient in coding in one or more languages such as Python/Java
• Experience in building solutions using cloud technologies like AWS
• Exposure to message streaming technologies such KAFKA/FLINK
• Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages.
• Overall knowledge of the Software Development Life Cycle
• Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)