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Tech Stack
Tools & technologiesPythonSQL
About the role
Key responsibilities & impact- Design, develop, and maintain crucial data infrastructure supporting credit risk models.
- Ensure data availability, accuracy, and reliability by collaborating with Quantitative modelers, experts, and stakeholders.
- Develop scalable data pipelines and integrate diverse sources.
- Ensure high data quality and governance with Data Stewards.
- Optimize and automate processes for efficient reporting and robust risk assessments, making a significant impact on analytical capabilities.
Requirements
What you’ll need- Proven experience as a Data Engineer, proficient in SQL, Python, and data modeling techniques, with a track record of working with large datasets.
- Knowledge of data warehousing concepts and best practices for data integration and storage.
- A strong understanding of data quality, security, and governance best practices.
- Familiarity with credit risk, Basel III, or other financial risk frameworks is a significant advantage.
- Demonstrated problem-solving abilities and strong communication skills for effective cross-team collaboration.
Benefits
Comp & perks- A diverse, inclusive and equal environment
- Extensive training and learning opportunities
- Hybrid work model, meaning remote work is possible up to 2 days/week
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
SQLPythondata modeling techniquesdata warehousingdata integrationdata storagedata qualitydata securitydata governancedata pipelines
Soft Skills
problem-solvingcommunicationcollaboration