Data Engineer
6 days ago
The Role:
- Integrate with internal/external LLM APIs (e.g., OpenAI, Azure OpenAI), including prompt engineering and pre/post-processing as required.
- Build and maintain data analysis workflows using Pandas for data transformation and insight delivery.
- Develop RESTful APIs using FastAPI or Flask for data and document management.
- Design and implement clean, efficient, and modular Python codebases for backend services, data pipelines, and document processing workflows.
- Support the team in onboarding new data sources, integrating with Azure services, and ensuring smooth cloud deployments.
- Collaborate with product, data science, and engineering teams to translate business requirements into technical solutions.
- Write unit tests and contribute to CI/CD pipelines for robust, production-ready code.
- Stay up to date with advances in Python, LLM, and cloud technologies.
Qualifications:
Bachelor's or master's in computer science, Engineering, or related quantitative discipline.
Experience:
6 to 9 years of hands-on experience in data engineering or backend development with Python.
Technical Competencies:
- Exposure to LLM integration (prompt design, API integration, handling text data).
- Strong experience in Python with focus on data analysis (Pandas) and scripting.
- Hands-on experience in building REST APIs (FastAPI or Flask).
- Experience in developing data pipelines, data cleaning, and transformation.
- Working knowledge of Azure cloud services (Azure Functions, Blob Storage, App Service, etc.)
(Nice to have) Experience integrating MongoDB with Python for data storage, modelling, or reporting.
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