Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
September 9, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
Unknown
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Pittsburgh, PA
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🧠 - Skills detailed
#SQL (Structured Query Language) #Spark SQL #Hadoop #Azure #GIT #AWS (Amazon Web Services) #Spark (Apache Spark) #Scala #Python #Data Governance #Datasets #GCP (Google Cloud Platform) #Cloud #Data Pipeline #"ETL (Extract #Transform #Load)" #Version Control #Logging #Observability #Batch #Data Engineering
Role description
Data Engineer (3 Openings)
Location: Pittsburgh, Cleveland, or Dallas (Hybrid: 3 days onsite)
Type: Contract-to-Hire
Clearance: US Citizen or Green Card Holder
Experience: 4–6 years
Key Responsibilities:
• Design and implement scalable data pipelines using Hadoop, Spark, and Hive
• Build and maintain ETL/ELT frameworks for batch and streaming data
• Collaborate with product teams to ingest, transform, and serve model-ready datasets
• Optimize data workflows for performance and reliability
• Ensure pipeline quality through validation, logging, and exception handling
Preferred Skills:
• Hadoop, Hive, Spark, SQL, Python
• Experience with version control (Git) and CI/CD tools
• Familiarity with modern data governance and observability practices
• Cloud experience a plus (AWS, Azure, GCP)
Data Engineer (3 Openings)
Location: Pittsburgh, Cleveland, or Dallas (Hybrid: 3 days onsite)
Type: Contract-to-Hire
Clearance: US Citizen or Green Card Holder
Experience: 4–6 years
Key Responsibilities:
• Design and implement scalable data pipelines using Hadoop, Spark, and Hive
• Build and maintain ETL/ELT frameworks for batch and streaming data
• Collaborate with product teams to ingest, transform, and serve model-ready datasets
• Optimize data workflows for performance and reliability
• Ensure pipeline quality through validation, logging, and exception handling
Preferred Skills:
• Hadoop, Hive, Spark, SQL, Python
• Experience with version control (Git) and CI/CD tools
• Familiarity with modern data governance and observability practices
• Cloud experience a plus (AWS, Azure, GCP)
