Zodiac Solutions, Inc
AI Data Engineer-Python & AI/ML
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AI Data Engineer with 15+ years of experience, focusing on Python and AI/ML, for a contract position in Bedford, TN (Remote). Retail domain experience is preferred. Key skills include ETL/ELT development and data modeling.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
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🗓️ - Date
July 16, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Remote
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
United States
-
🧠 - Skills detailed
#SQL (Structured Query Language) #Databases #Documentation #GIT #AI (Artificial Intelligence) #"ETL (Extract #Transform #Load)" #Databricks #Azure #Python #Data Science #Data Warehouse #Informatica #ADF (Azure Data Factory) #Microservices #Spark (Apache Spark) #REST (Representational State Transfer) #REST API #Deployment #Data Modeling #NoSQL #Snowflake #DevOps #Airflow #Security #Scala #Synapse #Datasets #Data Engineering #Dataflow #Data Lake #Apache Spark #Business Analysis #Data Governance #Monitoring #Data Pipeline #ML (Machine Learning) #PySpark #Cloud #Data Quality
Role description
Role: AI Data Engineer
Job Type: Contract
Location: Bedford, TN (Remote)
Mandatory Skills- Python, AI/ML
Retail domain experience is highly preferable.
JD:
We are seeking an experienced AI Data Engineer (15+ Years) to design, develop, and manage scalable data platforms that enable advanced analytics, Machine Learning (ML), and Generative AI solutions. The ideal candidate will build robust data pipelines, ensure data quality, and integrate AI/ML capabilities into enterprise data ecosystems.
Key Responsibilities
• Design, develop, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
• Build and optimize data lakes, data warehouses, and AI-ready data platforms.
• Develop ingestion, transformation, and orchestration frameworks using cloud-native technologies.
• Prepare, cleanse, and engineer datasets for AI/ML and Generative AI workloads.
• Integrate Large Language Models (LLMs), vector databases, embeddings, and RAG (Retrieval-Augmented Generation) pipelines into enterprise solutions.
• Implement data governance, security, lineage, and quality controls.
• Collaborate with Data Scientists, AI Engineers, Business Analysts, and Solution Architects.
• Monitor, troubleshoot, and optimize data pipelines and platform performance.
• Automate deployment, testing, and monitoring of data engineering workflows.
• Create technical documentation and data dictionaries for enterprise data assets.
Required Skills
Technical 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
Role: AI Data Engineer
Job Type: Contract
Location: Bedford, TN (Remote)
Mandatory Skills- Python, AI/ML
Retail domain experience is highly preferable.
JD:
We are seeking an experienced AI Data Engineer (15+ Years) to design, develop, and manage scalable data platforms that enable advanced analytics, Machine Learning (ML), and Generative AI solutions. The ideal candidate will build robust data pipelines, ensure data quality, and integrate AI/ML capabilities into enterprise data ecosystems.
Key Responsibilities
• Design, develop, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
• Build and optimize data lakes, data warehouses, and AI-ready data platforms.
• Develop ingestion, transformation, and orchestration frameworks using cloud-native technologies.
• Prepare, cleanse, and engineer datasets for AI/ML and Generative AI workloads.
• Integrate Large Language Models (LLMs), vector databases, embeddings, and RAG (Retrieval-Augmented Generation) pipelines into enterprise solutions.
• Implement data governance, security, lineage, and quality controls.
• Collaborate with Data Scientists, AI Engineers, Business Analysts, and Solution Architects.
• Monitor, troubleshoot, and optimize data pipelines and platform performance.
• Automate deployment, testing, and monitoring of data engineering workflows.
• Create technical documentation and data dictionaries for enterprise data assets.
Required Skills
Technical 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
