Job Description
We're seeking a highly skilled Senior Data Engineer to join our dynamic team. The ideal candidate will have extensive experience building robust data pipelines, integrating advanced AI technologies, and a strong background in Python and JavaScript.
Work Timings: US Time Zone
Job Type: Full-Time; Remote
Key Responsibilities:
Data Pipeline Development: Design, build, and maintain scalable data pipelines using Python and JavaScript.
Containerization: Deploy and manage containerized applications with Docker.
API Development: Develop and integrate RESTful services using FastAPI.
AI Integration: Collaborate with our AI team to implement generative AI models and LangChain technologies.
Security: Implement OAuth protocols for secure authentication and authorization.
Prompt Engineering: Optimize AI model performance through effective prompt engineering.
Analytics & OCR: Analyze complex datasets and integrate OCR technologies for data extraction.
Collaboration: Work closely with cross-functional teams to align data solutions with business objectives.
Must-Have Qualifications:
Experience: 5+ years in data engineering or a similar role.
Programming Skills: Proficient in Python and JavaScript.
Data Pipelines: Strong experience in building and optimizing data pipelines.
Docker: Hands-on experience with Docker containerization.
Generative AI: Familiarity with generative AI models and frameworks.
LangChain & FastAPI: Experience with LangChain and FastAPI.
RESTful Services: Proven ability to develop and consume RESTful APIs.
OAuth: Solid understanding of OAuth protocols.
Prompt Engineering: Expertise in crafting prompts for AI models.
Analytics: Strong analytical skills with experience in data analytics tools.
OCR: Knowledge of OCR technologies and their applications.
Bonus Skills
Workflow Management: Experience with tools like n8n, Apache Airflow, Cadence, or Temporal.
Cloud Services: Familiarity with Google Cloud Platform and Firebase.
LangGraph & Agentic Flows: Experience with LangGraph and designing agentic flows.
Kubernetes: Knowledge of Kubernetes for container orchestration.
Microservices: Understanding of microservices architecture and deployment.
