You thrive on diversity and creativity, and we welcome individuals who share our vision of making a lasting impact. Your unique combination of design thinking and experience will help us achieve new heights.
As a Data Engineer II at JPMorgan Chase within the Asset & Wealth Management, youare part of an agile team that works to enhance, design, and deliver the data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. As an emerging member of a data engineering team, you execute data 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.
Job responsibilities
- Organizes, updates, and maintains gathered data that will aid in making the data actionable
- Demonstrates basic knowledge of the data system components to determine controls needed to ensure secure data access
- Be responsible for making custom configuration changes in one to two tools to generate a product at the business or customer request
- Updates logical or physical data models based on new use cases with minimal supervision
- Adds to team culture of diversity, equity, inclusion, and respect
Required qualifications, capabilities, and skills
- Formal training or certification onData engineeringconcepts and 2+ years applied experience
- Proven experience managing the full lifecycle of data, from collection and storage to analysis.
- Proficiency in Python for data manipulation and analysis.
- Proficiencywith major cloud platforms such as AWS and Snowflake. Familiarity with ETL tools, including Spark and Databricks.
- Extensive knowledge of database management systems and data modelling. Understanding of SQL and NoSQL database concepts.
- Knowledge of Data Mesh, data modeling, and domain-driven design. Experience with version control systems and tools, including Git, GitHub, GitLab, and Bitbucket.
- Demonstrated ability in statistical data analysis, selecting appropriate tools and identifying relevant data patterns for comprehensive analysis.
- Experience implementing custom changes in tools to produce tailored data products.
