Domo BI

3 weeks ago


india, IN EXL Full time

We are looking for a talented Data Engineer with expertise in SAS and Google Cloud Platform (GCP) to join our team. The ideal candidate will have a strong background in the Credit Risk domain and will be responsible for designing, building, and optimising data pipelines and architectures to support credit risk analysis and reporting. Key Responsibilities: Data Pipeline Development: Design, develop, and maintain data pipelines using SAS and GCP to ensure efficient data processing and integration. Data Architecture: Build and optimise data architectures to support credit risk analysis and reporting. Data Management: Manage and manipulate large datasets to support credit risk modelling and analysis. Collaboration: Work closely with data scientists, analysts, and other stakeholders to gather requirements and provide data solutions. Performance Optimisation: Optimise data processing performance to ensure timely and accurate reporting. Compliance: Ensure all data processes comply with regulatory standards and guidelines. Documentation: Maintain comprehensive documentation of data processes and methodologies. Required Skills and Qualifications: Technical Skills: Proficiency in SAS and Google Cloud Platform (GCP) is essential. Domain Knowledge: Strong understanding of the Credit Risk domain. Data Engineering: Experience in designing and building data pipelines and architectures. Analytical Skills: Excellent analytical and problem-solving skills with the ability to perform complex data analysis. Attention to Detail: High level of accuracy and attention to detail in data processing and analysis. Communication Skills: Strong verbal and written communication skills to effectively convey findings and recommendations. Experience: Previous experience in data engineering or a related field is preferred. Education: Bachelor's degree in Computer Science, Data Science, Engineering, or a related field. Advanced degrees or certifications in Data Engineering or related areas are a plus.


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