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Job Description

Overview
Enterprise64 is a U.S.-based technology company that creates digital solutions for startups to Fortune 500 companies in the United States, Europe, and the United Arab Emirates. We are growing rapidly across all our global offices and have career opportunities for tech professionals who are looking to work in a fast-growing company, work in a fun environment, looking to be challenged, grow, and fast-track their careers.
Job Overview

We are hiring a Data Engineer with expertise in Vector Databases and AI-driven data pipelines to support our Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems. This role focuses on designing, optimizing, and maintaining scalable AI data infrastructure, ensuring seamless integration between LLMs and high-performance retrieval mechanisms. The Data Engineer will work closely with our Senior Data Scientist and AI/ML Engineer to build efficient AI-powered data storage and retrieval solutions that enhance the speed, accuracy, and scalability of our AI models. 


Key Responsibilities:
  • Strong knowledge of RDBMS, NoSQL and Vector databases with handson experice of  OLTP and OLAP. 
  • Strong knowledge of ETL pipelines through SQL (Stored Procedures), PySpark and Pandas with batch and realtime data procssing. 
  • Strong knowledge of Azure (ADF/Synappse/Datalake Gen2) or AWS (S3, Glue, Redshift, Lambda). 
  • Strong knowledge of python with fast, flask or Django. 
  • Strong knowledge of data orchestration like Apache Airflow, Prefect and Kafka. 
  • Strong knowledge of schema design, normalization/ denormalization, data warehousing. 
  • Integration AI models in data pipeline. 
  • Skill of Power BI is plus. 
  • Caching through Redis is plus.
Preferred Qualifications:
  • Proficiency in Python for data engineering and AI model integration.  
  • Hands-on experience with Vector Databases (FAISS, Pinecone, Weaviate, Milvus).  
  • Strong knowledge of data storage, indexing, and retrieval optimization.  
  • Experience building data pipelines for AI-powered applications.  
  • Familiarity with embedding models and vectorized search techniques.  
  • Understanding of distributed data architectures and scalable AI storage solutions.  
  • Experience with cloud-based AI infrastructure (AWS, GCP, Azure) is a plus.  
  • Data modeling and Schema.
Benefits
  • Talent upskilling program.
  • Provident fund.   
  • Health insurance.
  • Eligible for US H-1 Visa.   
  • Project-based bonus.  
  • Leave encashment.   
  • EOBI
  • Maternity leaves/ Paternal WFH  
  • Religious holidays   
  • Work from home facility.
  • Referral bonus.
  • Shared success reward.  
  • Paid time off.  
  • Transportation service. 
  • Loan and advance salary. 

 

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