Resource Logistics Inc.
AI Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AI Data Engineer with a contract length of "unknown", offering a pay rate of "unknown". Key skills include Python, SQL, PySpark, ETL/ELT development, and retail domain experience is highly preferable.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
440
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🗓️ - Date
July 16, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Unknown
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📄 - Contract
Unknown
-
🔒 - Security
Unknown
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📍 - Location detailed
Tennessee, United States
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🧠 - Skills detailed
#SQL (Structured Query Language) #Databases #GIT #AI (Artificial Intelligence) #"ETL (Extract #Transform #Load)" #Databricks #Azure #Python #Informatica #ADF (Azure Data Factory) #Microservices #Spark (Apache Spark) #REST (Representational State Transfer) #REST API #Data Modeling #NoSQL #Snowflake #DevOps #Airflow #Synapse #Data Engineering #Dataflow #Apache Spark #ML (Machine Learning) #PySpark
Role description
Mandatory Skills- Python, AI/ML
Retail domain experience is highly preferable.
Required Skills:
• Python, SQL, PySpark
• ETL/ELT development
• Data Modeling (Star Schema, Snowflake Schema)
• Apache Spark, Databricks
• Airflow, Dataflow, Informatica, ADF, Synapse, or equivalent tools
• Relational & NoSQL Databases
• Data Warehousing concepts
• REST APIs and Microservices
• Git, CI/CD, DevOps practices
AI & GenAI Skills:
• Machine Learning fundamentals
• Data preparation for AI models
• Vector Databases (Pinecone, ChromaDB, FAISS)
• LLM Integration (OpenAI, Azure OpenAI, Gemini, Claude, etc.)
• RAG Architecture
• Embeddings and Semantic Search
• Prompt Engineering fundamentals
Mandatory Skills- Python, AI/ML
Retail domain experience is highly preferable.
Required Skills:
• Python, SQL, PySpark
• ETL/ELT development
• Data Modeling (Star Schema, Snowflake Schema)
• Apache Spark, Databricks
• Airflow, Dataflow, Informatica, ADF, Synapse, or equivalent tools
• Relational & NoSQL Databases
• Data Warehousing concepts
• REST APIs and Microservices
• Git, CI/CD, DevOps practices
AI & GenAI Skills:
• Machine Learning fundamentals
• Data preparation for AI models
• Vector Databases (Pinecone, ChromaDB, FAISS)
• LLM Integration (OpenAI, Azure OpenAI, Gemini, Claude, etc.)
• RAG Architecture
• Embeddings and Semantic Search
• Prompt Engineering fundamentals
