Data Solutions Architect

3 days ago


Singapore beBeeDataAnalytics Full time $180,000 - $240,000
Data Analytics Developer

About the Role:

  • We are seeking an experienced Data Analyst to join our team. This role involves designing, building, and deploying analytics solutions that enhance innovation and deliver business value.

Key Responsibilities:

  • Design, develop, and maintain end-to-end analytics solutions in collaboration with cross-functional teams.
  • Write high-quality, maintainable, and well-documented code adhering to best software engineering standards.
  • Develop and optimize data pipelines, ensuring efficient and secure integration from varied sources.
  • Build intelligent, API-driven services for diverse business use cases using Python and modern AI frameworks.
  • Utilize tools and libraries like Pandas and Pydantic for building robust data pipelines.
  • Implement machine learning and analytics solutions with monitoring for model performance, data drift, and system observability.
  • Manage deployment using containerization and workflow orchestration tools.
  • Integrate services with cloud platforms and develop microservices architectures with scalable RESTful or GraphQL APIs.
  • Ensure solutions comply with security, privacy, and responsible AI standards.
  • Keep up-to-date with trends and best practices in AI, analytics, and software development.

Requirements:

  • Bachelor's or Master's degree in Computer Science, Engineering, or related fields.
  • Strong problem-solving ability and capability to communicate technical information to non-technical stakeholders.
  • Proficient in software engineering principles and experienced with multiple programming languages such as Python, Java, or JavaScript.
  • Hands-on experience with AI/ML frameworks and building production-grade data pipelines following DataOps and MLOps practices.
  • Familiarity with containerization (Docker, Kubernetes) and CI/CD pipeline automation.
  • Experience with modern web development and building scalable APIs.
  • Knowledge of cloud platforms (preferred but not specific).
  • Understanding of security, privacy, and regulatory compliance within AI/ML contexts.
  • Prior exposure to regulated industries or financial services is a plus.
  • Comfortable using data visualization and team collaboration tools.

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