AI Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AI Data Engineer in Philadelphia, PA, on a contract basis. Key skills include Python, AWS, ETL, and NLP. Experience with data ingestion, cleaning, and transformation for AI is required. Understanding of vector databases is a plus.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
September 4, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
On-site
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Philadelphia, PA
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🧠 - Skills detailed
#Data Ingestion #Libraries #"ETL (Extract #Transform #Load)" #AI (Artificial Intelligence) #Docker #Data Profiling #Databases #Python #Kubernetes #Data Engineering #AWS (Amazon Web Services) #NLP (Natural Language Processing) #Data Cleaning
Role description
Role: AI Data Engineer (AIRE)
Location: Philadelphia, PA (Onsite)
Duration: Contract
Job Description:
• Experience in Data Ingestion and integration from various sources and experience building automated ingestion pipelines using AWS
• Experience in Data cleaning, processing and transformation for unstructured and semi-structured data
• Experience preparing data for AI usage and experience with data profiling/quality—identify data gaps and inconsistencies.
• Tools - Strong Python, ETL libraries, SQLs, Docker/Kubernetes, Experience with some AWS Data/Pipeline Services, some exposure to NLP processing, experience with one vector DB
• Some Understanding of NLP processing - parsing, chunking, splitting, and tokenization
• Some understanding of vector databases and embedding
• Any experience working with a graph database is a plus
Role: AI Data Engineer (AIRE)
Location: Philadelphia, PA (Onsite)
Duration: Contract
Job Description:
• Experience in Data Ingestion and integration from various sources and experience building automated ingestion pipelines using AWS
• Experience in Data cleaning, processing and transformation for unstructured and semi-structured data
• Experience preparing data for AI usage and experience with data profiling/quality—identify data gaps and inconsistencies.
• Tools - Strong Python, ETL libraries, SQLs, Docker/Kubernetes, Experience with some AWS Data/Pipeline Services, some exposure to NLP processing, experience with one vector DB
• Some Understanding of NLP processing - parsing, chunking, splitting, and tokenization
• Some understanding of vector databases and embedding
• Any experience working with a graph database is a plus
