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Job Summary: We are seeking a Data Engineer with expertise in AI-driven analytics to design and build scalable data systems that support advanced analytics and machine learning use cases. This role focuses on developing robust data pipelines, managing modern data storage solutions, and enabling high-quality data for AI models within a cloud-based environment. The ideal candidate will have strong experience with Python, SQL, and Azure, along with exposure to AI frameworks and vector databases. Key Responsibilities: Design and build scalable data ingestion, transformation, and processing pipelines for AI and machine learning applications. Develop and maintain data storage solutions, including vector databases, to support Retrieval-Augmented Generation (RAG). Implement data lineage, validation, and security controls to ensure data quality and reliability. Clean, structure, and prepare complex datasets for analytical and operational use. Support AI-driven analytics and mapping use cases. Work extensively within Azure cloud environments to build and manage data solutions. Collaborate with cross-functional teams to deliver scalable and efficient data architectures. Required Qualifications: 5 years of experience with strong proficiency in SQL and Python. 5 years of experience working in Azure cloud environments. 5 years of experience in AI-driven analytics or related data engineering roles. Experience with ETL/ELT pipeline design and data warehousing. Familiarity with AI tools and frameworks such as vector databases (e.g., Pinecone, Milvus) and frameworks like Hugging Face or LangChain. Strong understanding of data architecture, data modeling, and scalable system design. Bachelors degree in Computer Science or equivalent work experience. Preferred Qualifications: Experience working with advanced AI/ML pipelines and data platforms. Exposure to Retrieval-Augmented Generation (RAG) architectures. Familiarity with data governance, security, and compliance best practices in cloud environments. Education: Bachelors Degree
Job Summary: We are seeking a Data Engineer with expertise in AI-driven analytics to design and build scalable data systems that support advanced analytics and machine learning use cases. This role focuses on developing robust data pipelines, managing modern data storage solutions, and enabling high-quality data for AI models within a cloud-based environment. The ideal candidate will have strong experience with Python, SQL, and Azure, along with exposure to AI frameworks and vector databases. Key Responsibilities: Design and build scalable data ingestion, transformation, and processing pipelines for AI and machine learning applications. Develop and maintain data storage solutions, including vector databases, to support Retrieval-Augmented Generation (RAG). Implement data lineage, validation, and security controls to ensure data quality and reliability. Clean, structure, and prepare complex datasets for analytical and operational use. Support AI-driven analytics and mapping use cases. Work extensively within Azure cloud environments to build and manage data solutions. Collaborate with cross-functional teams to deliver scalable and efficient data architectures. Required Qualifications: 5 years of experience with strong proficiency in SQL and Python. 5 years of experience working in Azure cloud environments. 5 years of experience in AI-driven analytics or related data engineering roles. Experience with ETL/ELT pipeline design and data warehousing. Familiarity with AI tools and frameworks such as vector databases (e.g., Pinecone, Milvus) and frameworks like Hugging Face or LangChain. Strong understanding of data architecture, data modeling, and scalable system design. Bachelors degree in Computer Science or equivalent work experience. Preferred Qualifications: Experience working with advanced AI/ML pipelines and data platforms. Exposure to Retrieval-Augmented Generation (RAG) architectures. Familiarity with data governance, security, and compliance best practices in cloud environments. Education: Bachelors Degree