Synthetic 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 16, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
Hybrid
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Minneapolis, MN
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🧠 - Skills detailed
#Python #Data Governance #Data Pipeline #GitLab #Redshift #S3 (Amazon Simple Storage Service) #Metadata #Security #Cloud #AWS (Amazon Web Services) #Data Engineering #Compliance #Classification #AI (Artificial Intelligence)
Role description
T+S
USC/GC
hybrid day 1 need local
We are seeking a Synthetic Data Engineer with strong expertise in Test Data Using AI Tools, AWS, and Data Governance. In this role, you’ll help design and maintain synthetic data pipelines, ensure privacy compliance, and support enterprise data initiatives across cloud environments.
What You’ll Do
• Build integrations with Datalog tools for metadata and classification alignment.
• Develop Python scripts and custom APIs to automate data workflows.
• Automate pipelines via GitLab CI/CD, orchestrating data flows across Redshift, S3.
• Collaborate with security teams to enforce data governance & compliance.
• Validate synthetic data fidelity and performance across staging/test environments.
• Hands-on Tonic AI in AWS for synthetic & de-identified data.
T+S
USC/GC
hybrid day 1 need local
We are seeking a Synthetic Data Engineer with strong expertise in Test Data Using AI Tools, AWS, and Data Governance. In this role, you’ll help design and maintain synthetic data pipelines, ensure privacy compliance, and support enterprise data initiatives across cloud environments.
What You’ll Do
• Build integrations with Datalog tools for metadata and classification alignment.
• Develop Python scripts and custom APIs to automate data workflows.
• Automate pipelines via GitLab CI/CD, orchestrating data flows across Redshift, S3.
• Collaborate with security teams to enforce data governance & compliance.
• Validate synthetic data fidelity and performance across staging/test environments.
• Hands-on Tonic AI in AWS for synthetic & de-identified data.
