Alasus Technologies
Responsibilities
Design, build, and maintain scalable backend applications using Python and the Django framework. Implement RESTful APIs and integrate third‑party services. Deploy models and data applications on AWS or similar cloud platforms. Work closely with business analysts and data scientists to automate financial workflows and support underwriting and credit modeling. Optimize code for performance and scalability; participate in code reviews and collaborative design discussions. Work with relational and NoSQL databases (PostgreSQL, Oracle, MongoDB, etc.) and optimize database queries. Support Full Software Development Lifecycle
Requirement gathering, architecture, development, testing, deployment, and documentation. Employ version control (Git), CI/CD pipelines, containerization (Jenkins, Docker, Kubernetes), and deployment, and automated testing best practices. Troubleshoot and maintain core data pipelines and APIs for loss mitigation, credit models, and financial services applications. Qualifications
Bachelor’s or master’s degree in computer science, engineering, or related quantitative field. 6+ years’ experience in professional software development with Python and Django required (preferably in finance, data, or enterprise domains). Deep knowledge of Python libraries (NumPy, Pandas), REST API development, and backend system integration. Cloud deployment experience (AWS preferred); Docker, Jenkins, and CI/CD tools highly desired. SQL database expertise (PostgreSQL, MySQL) and understanding of data ETL concepts. Experience with frontend technologies (Angular, React, JavaScript) is a plus. Strong communication skills and ability to work in cross‑functional Agile team. Commitment to security, privacy, and regulatory standards. Key Skills Highlight: Python programming: Advanced proficiency in software development and scripting; Django framework: Building REST APIs, scalable web applications, and modular backend systems; Cloud technologies: Experience with AWS or comparable cloud platforms for deployment and scaling; Database management: Work with relational and NoSQL databases (PostgreSQL, Oracle, MongoDB, etc.) and optimize database queries. Version Control and CI/CD
Git (GitHub Actions, GitLab CI), Jenkins, Docker, Kubernetes for seamless development workflows. Containerization
Familiarity with containerization (Docker, Kubernetes). Automated Testing
Unit, integration, and system testing for reliable code. Data Analysis Libraries
Experience with Pandas, NumPy, and related tools. Preferred Experience
Experience in financial services / mortgage industry or highly regulated environments. Asynchronous Frameworks
Knowledge of asynchronous frameworks (Celery, RabbitMQ, Kafka). Front-end Frameworks
Familiarity with front-end frameworks (React, Angular, or Vue.js). Data Engineering / ML Integration
Exposure to data engineering or machine learning integration with Python. Security Best Practices
Understanding of security best practices (OAuth2, JWT, SSL, SAML).
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Design, build, and maintain scalable backend applications using Python and the Django framework. Implement RESTful APIs and integrate third‑party services. Deploy models and data applications on AWS or similar cloud platforms. Work closely with business analysts and data scientists to automate financial workflows and support underwriting and credit modeling. Optimize code for performance and scalability; participate in code reviews and collaborative design discussions. Work with relational and NoSQL databases (PostgreSQL, Oracle, MongoDB, etc.) and optimize database queries. Support Full Software Development Lifecycle
Requirement gathering, architecture, development, testing, deployment, and documentation. Employ version control (Git), CI/CD pipelines, containerization (Jenkins, Docker, Kubernetes), and deployment, and automated testing best practices. Troubleshoot and maintain core data pipelines and APIs for loss mitigation, credit models, and financial services applications. Qualifications
Bachelor’s or master’s degree in computer science, engineering, or related quantitative field. 6+ years’ experience in professional software development with Python and Django required (preferably in finance, data, or enterprise domains). Deep knowledge of Python libraries (NumPy, Pandas), REST API development, and backend system integration. Cloud deployment experience (AWS preferred); Docker, Jenkins, and CI/CD tools highly desired. SQL database expertise (PostgreSQL, MySQL) and understanding of data ETL concepts. Experience with frontend technologies (Angular, React, JavaScript) is a plus. Strong communication skills and ability to work in cross‑functional Agile team. Commitment to security, privacy, and regulatory standards. Key Skills Highlight: Python programming: Advanced proficiency in software development and scripting; Django framework: Building REST APIs, scalable web applications, and modular backend systems; Cloud technologies: Experience with AWS or comparable cloud platforms for deployment and scaling; Database management: Work with relational and NoSQL databases (PostgreSQL, Oracle, MongoDB, etc.) and optimize database queries. Version Control and CI/CD
Git (GitHub Actions, GitLab CI), Jenkins, Docker, Kubernetes for seamless development workflows. Containerization
Familiarity with containerization (Docker, Kubernetes). Automated Testing
Unit, integration, and system testing for reliable code. Data Analysis Libraries
Experience with Pandas, NumPy, and related tools. Preferred Experience
Experience in financial services / mortgage industry or highly regulated environments. Asynchronous Frameworks
Knowledge of asynchronous frameworks (Celery, RabbitMQ, Kafka). Front-end Frameworks
Familiarity with front-end frameworks (React, Angular, or Vue.js). Data Engineering / ML Integration
Exposure to data engineering or machine learning integration with Python. Security Best Practices
Understanding of security best practices (OAuth2, JWT, SSL, SAML).
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