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Synthetic Data Engineer Jobs (NOW HIRING)

Data Engineer

Buffalo, NY · On-site

$70 - $75/hr

Title : Data Engineer Duration: 12 months+ Open Contract Location: Buffalo, NY remote Interview ... Synthetic data generation * Experience with cloud platforms (Azure strongly preferred) * Ability to ...

... synthetic data generation and data privacy at scale, including context-aware anonymization ... This role combines hands-on software engineering with applied research in LLMs and privacy ...

Platform Engineer, Data

Austin, TX · On-site

$113K - $136K/yr

You'll partner closely with our ML engineers to orchestrate ingestion, synthetic data generation, and versioned releases, ensuring that every dataset is not only high-integrity and available but ...

Platform Engineer, Data

Austin, TX · On-site

$113K - $136K/yr

You'll partner closely with our ML engineers to orchestrate ingestion, synthetic data generation, and versioned releases, ensuring that every dataset is not only high-integrity and available but ...

Platform Engineer, Data

Austin, TX · On-site

$113K - $136K/yr

You'll partner closely with our ML engineers to orchestrate ingestion, synthetic data generation, and versioned releases, ensuring that every dataset is not only high-integrity and available but ...

Experience in data engineering, synthetic data pipelines, ETL/ELT workflows, or regulated healthcare data systems. * Compliance Knowledge: Familiarity with PI/PHI handling, HIPAA, or regulated‑data ...

Platform Engineer, Data

Austin, TX · On-site

$113K - $136K/yr

You'll partner closely with our ML engineers to orchestrate ingestion, synthetic data generation, and versioned releases, ensuring that every dataset is not only high-integrity and available but ...

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Synthetic Data Engineer information

See salary details

$44.5K

$129.7K

$177.5K

How much do synthetic data engineer jobs pay per year?

As of Jun 29, 2026, the average yearly pay for synthetic data engineer in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What is the difference between Synthetic Data Engineer vs Data Scientist?

AspectSynthetic Data EngineerData Scientist
Required CredentialsBachelor's or higher in CS, Data Science, or related fields; experience with data generation toolsBachelor's or higher in Statistics, Data Science, or related fields; proficiency in programming and analytics
Work EnvironmentFocus on data generation, privacy, and simulation in tech or finance industriesData analysis, modeling, and insights across various industries
Employer & Industry UsageTech companies, finance, healthcare for privacy-preserving dataResearch institutions, tech firms, healthcare, marketing

While Synthetic Data Engineers specialize in creating artificial data for privacy and testing, Data Scientists analyze real data to extract insights. Both roles require strong technical skills, but their focus areas differ—one on data generation, the other on data analysis.

Which 3 jobs will survive AI?

Synthetic Data Engineers are likely to continue to be in demand as AI development relies on high-quality synthetic data for training models. Roles involving complex problem-solving, creative tasks, and human interaction—such as AI specialists, data scientists, and cybersecurity analysts—are also expected to persist due to their reliance on nuanced judgment and expertise. These jobs require specialized skills and adapt to evolving AI tools, making them more resilient to automation.

What is a synthetic data engineer?

A synthetic data engineer is a professional who designs and develops artificial data that mimics real datasets for use in machine learning, testing, and data analysis. They often work with data generation tools, programming languages like Python, and focus on privacy-preserving data creation to support AI development and model training.

Is AI taking over data engineer jobs?

AI and automation are transforming data engineering by automating tasks such as data cleaning, integration, and pipeline management. However, data engineers are still essential for designing, maintaining, and overseeing complex data systems, and their expertise in tools like SQL, Python, and cloud platforms remains in demand.

What is the salary of a synthetic data engineer?

The salary of a synthetic data engineer typically ranges from $80,000 to $150,000 annually, depending on experience, location, and company size. Professionals with skills in data modeling, machine learning, and programming languages like Python or SQL tend to earn higher salaries.
What cities are hiring for Synthetic Data Engineer jobs? Cities with the most Synthetic Data Engineer job openings:
What states have the most Synthetic Data Engineer jobs? States with the most job openings for Synthetic Data Engineer jobs include:
Data Engineer

$70 - $75/hr

Other

Posted 3 days ago


Job description

Location: Buffalo, NY Salary: $70.00 USD Hourly - $75.00 USD Hourly Description:
Title : Data Engineer
Duration: 12 months+ Open Contract
Location: Buffalo, NY remote
Interview information: Single 90-minute technical interview
Must Haves:
  • Project Management
  • Strong database experience:
    • DDL / DML
    • Data querying, insertion, and manipulation
  • Strong programming foundation (language-agnostic mindset):
    • Java, Python, Ruby, or JavaScript/TypeScript
  • Experience with:
    • CI/CD pipelines (GitLab preferred)
    • Git/version control
  • Experience with APIs (consumption and integration)
  • Solid understanding of:
    • Test data management
    • Data obfuscation / masking
    • Synthetic data generation
  • Experience with cloud platforms (Azure strongly preferred)
  • Ability to work with and across:
    • Legacy systems
    • Modern cloud environments
  • Strong communication skills (working with app teams, stakeholders)
  • Ability to operate as a self-starter in a fast-paced environment

Nice to Haves:
  • Experience with Delphix (DCT / Compliance Tool) or similar:
    • Broadcom or other data masking solutions
  • Containerization experience:
    • Docker
    • Kubernetes (basic understanding is sufficient)
  • Exposure to quality assurance/testing practices
  • Financial services experience (highly preferred)
    • Data conditioning within banking environments
  • Experience with mainframe systems:
    • VSAM files or legacy data platforms
  • Familiarity with AI-assisted tools (Copilot, GitLab Duo)

Key Responsibilities:
  • Support enterprise test data management initiatives
  • Perform data obfuscation/masking for non-production environments
  • Enable synthetic data generation to reduce use of sensitive data
  • Work across:
    • Databases
    • APIs
    • Mainframe and cloud systems
  • Support teams requesting test data across the bank
  • Integrate data processes into CI/CD pipelines

Ideal Candidate Traits:
  • Able to communicate effectively across all levels (technical & leadership)
  • Adaptable in a mixed/legacy + modern tech environment
  • Confident in technical knowledge (can explain decisions clearly)
  • Strong ability to understand the "big picture"
  • Comfortable working in complex enterprise ecosystems

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This job and many more are available through The Judge Group. Please apply with us today!