Data Engineer III – Cybersecurity Technology Resiliency
| Company | JP Morgan Chase |
|---|---|
| Location | Wilmington, DE, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | Bachelor’s |
| Experience Level | Mid Level, Senior |
Requirements
- Formal training or certification on data engineering concepts and 3+ years applied experience.
- Experience across the data lifecycle
- Advanced at SQL (e.g., joins and aggregations)
- Experience with data structures, such as NoSQL, OTF, and RDMS.
- Significant experience with statistical data analysis and ability to determine appropriate tools and data patterns to perform analysis
- Experience customizing changes in a tool to generate product
- Experience with various database technologies, such as MySQL, PostgreSQL, and MongoDB.
- Experience with analytics engines/platforms, such as Apache Spark and Hadoop.
- Experience with data migration and mapping complex relational data between business systems.
Responsibilities
- Supports review of controls to ensure sufficient protection of enterprise data
- Advises and makes 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
- Utilize SQL and understands NoSQL databases and their niche in the marketplace
- Manage & optimize databases for performance and efficiency.
- Design & build data pipelines that clean, transform, and aggregate data from disparate sources.
- Develop new models that can be used to make predictions and answer questions for the overall business.
- Contribute to a team culture that values diversity, equity, inclusion, and respect.
Preferred Qualifications
- Degree, or equivalent practical experience, in Computer Science, Information Systems, Data Science, or a related field.
- Exceptional analytical skills with the ability to translate business requirements into data engineering solutions.
- Experience of data science methods including statistical and analytical techniques.
- Experience in Data Mining techniques used in data science and data analytics.
- Excellent problem-solving abilities, attention to detail, and ability to work independently or in a team.
- Effective communication and interpersonal skills to foster relationships with stakeholders at all levels.
- Advocate for driving efficiencies, stabilization, and continuous improvement.