CONFLUX SYSTEMS
AI Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AI Data Engineer in Charlotte, NC, on a contract basis. It requires 5+ years of data engineering experience, proficiency in Python and SQL, and expertise in Generative AI and cloud platforms.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
408
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🗓️ - Date
June 12, 2026
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
W2 Contractor
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🔒 - Security
Unknown
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📍 - Location detailed
Charlotte, NC
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🧠 - Skills detailed
#PySpark #"ETL (Extract #Transform #Load)" #REST (Representational State Transfer) #Computer Science #Data Pipeline #AWS (Amazon Web Services) #Data Lake #Kafka (Apache Kafka) #AI (Artificial Intelligence) #Data Warehouse #GCP (Google Cloud Platform) #ML (Machine Learning) #Python #Databases #Security #SQL (Structured Query Language) #Data Processing #Data Science #Data Quality #Apache Spark #Microservices #Scala #Langchain #REST API #Cloud #Monitoring #Spark (Apache Spark) #Azure #Data Engineering #Data Integration
Role description
Job Title: Data Engineer with GenAI
Location: Charlotte, NC (Day 1 Onsite)
Employment Type: Contract/ W2
Job Summary
We are seeking a highly skilled Data Engineer with Generative AI expertise to join our team in Charlotte, NC. The ideal candidate will have strong experience in data engineering, cloud platforms, data pipelines, and modern AI/ML technologies, including Large Language Models (LLMs) and Generative AI solutions. This role requires working closely with data scientists, AI engineers, and business stakeholders to build scalable data platforms and AI-powered applications.
Key Responsibilities
Design, develop, and maintain scalable data pipelines and ETL/ELT processes.
Build and optimize data lakes, data warehouses, and real-time data processing solutions.
Integrate structured and unstructured data sources to support AI/ML and GenAI use cases.
Develop and support Retrieval-Augmented Generation (RAG) architectures and vector database implementations.
Collaborate with AI/ML teams to prepare and engineer data for model training, fine-tuning, and inference.
Implement data quality, governance, security, and monitoring frameworks.
Build APIs and data services to support GenAI applications and enterprise integrations.
Optimize data processing workflows for performance, scalability, and cost efficiency.
Work with cloud-native technologies and modern data engineering frameworks.
Partner with stakeholders to understand business requirements and translate them into technical solutions.
Required Qualifications
Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or related field.
5+ years of experience in Data Engineering.
Strong proficiency in Python, SQL, and data processing frameworks.
Hands-on experience with Apache Spark, PySpark, Kafka, and distributed data systems.
Experience building ETL/ELT pipelines using modern data integration tools.
Strong knowledge of data warehousing concepts and dimensional modeling.
Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).
Experience working with Generative AI, Large Language Models (LLMs), and AI application development.
Familiarity with LangChain, LlamaIndex, Prompt Engineering, and RAG frameworks.
Experience with vector databases such as Pinecone, Weaviate, Chroma, or FAISS.
Understanding of REST APIs, microservices, and containerization technologies.
Strong problem-solving, analytical, and communication skills.
Job Title: Data Engineer with GenAI
Location: Charlotte, NC (Day 1 Onsite)
Employment Type: Contract/ W2
Job Summary
We are seeking a highly skilled Data Engineer with Generative AI expertise to join our team in Charlotte, NC. The ideal candidate will have strong experience in data engineering, cloud platforms, data pipelines, and modern AI/ML technologies, including Large Language Models (LLMs) and Generative AI solutions. This role requires working closely with data scientists, AI engineers, and business stakeholders to build scalable data platforms and AI-powered applications.
Key Responsibilities
Design, develop, and maintain scalable data pipelines and ETL/ELT processes.
Build and optimize data lakes, data warehouses, and real-time data processing solutions.
Integrate structured and unstructured data sources to support AI/ML and GenAI use cases.
Develop and support Retrieval-Augmented Generation (RAG) architectures and vector database implementations.
Collaborate with AI/ML teams to prepare and engineer data for model training, fine-tuning, and inference.
Implement data quality, governance, security, and monitoring frameworks.
Build APIs and data services to support GenAI applications and enterprise integrations.
Optimize data processing workflows for performance, scalability, and cost efficiency.
Work with cloud-native technologies and modern data engineering frameworks.
Partner with stakeholders to understand business requirements and translate them into technical solutions.
Required Qualifications
Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or related field.
5+ years of experience in Data Engineering.
Strong proficiency in Python, SQL, and data processing frameworks.
Hands-on experience with Apache Spark, PySpark, Kafka, and distributed data systems.
Experience building ETL/ELT pipelines using modern data integration tools.
Strong knowledge of data warehousing concepts and dimensional modeling.
Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).
Experience working with Generative AI, Large Language Models (LLMs), and AI application development.
Familiarity with LangChain, LlamaIndex, Prompt Engineering, and RAG frameworks.
Experience with vector databases such as Pinecone, Weaviate, Chroma, or FAISS.
Understanding of REST APIs, microservices, and containerization technologies.
Strong problem-solving, analytical, and communication skills.
