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Contract Data Engineering Jobs in Berkeley, CA (NOW HIRING)

Cloud BC Labs

AWS Data Engineer

Alameda, CA · On-site

$129K - $155K/yr

Contract to hire or FTE Experience: 10 to max 20 Mandatory - need summary on pharma and commercial ... Minimum of 8 years of experience in data engineering with a focus on AWS data services. Skills:

Mill

Data Engineer - Data Platform

San Bruno, CA · On-site

$185K - $210K/yr

... engineering, data analytics, and marketing teams. What You'll Do * Design, build, and maintain ... Familiarity with data contract or data mesh patterns, or RBAC/access governance on a warehouse

New

Mill

Data Engineer - Data Platform

San Bruno, CA

$185K - $210K/yr

... engineering, data analytics, and marketing teams. What You'll Do * Design, build, and maintain ... Familiarity with data contract or data mesh patterns, or RBAC/access governance on a warehouse

New

Vertex Sigma Software

Data Engineer

Foster City, CA · On-site

$133K - $160K/yr

AV Safety Data Engineer (Contract) The Safety Strategy & Operations team is responsible for developing and implementing safety processes from comprehensive safety planning and risk management to ...

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Showing results 21-40

All JobsContract Data Engineering JobsContract Data Engineering Jobs in Berkeley, CA

Contract Data Engineering information

See Berkeley, CA salary details

$54.5K

$158.8K

$217.3K

How much do contract data engineering jobs pay per year?

As of Aug 22, 2026, the average yearly pay for contract data engineering in Berkeley, CA is $158,830.00, according to ZipRecruiter salary data. Most workers in this role earn between $140,200.00 and $168,400.00 per year, depending on experience, location, and employer.

What is contract data engineering?

Contract data engineering refers to hiring data engineers on a temporary or project basis, rather than as full-time employees. Contract data engineers are responsible for designing, building, and maintaining data pipelines, databases, and other infrastructure to support data analytics and business needs. Companies often hire contract data engineers to handle specific projects, scale up teams quickly, or bring in specialized skills for a limited time. This arrangement offers flexibility for both the company and the engineer, and is common in industries with fluctuating data workloads or short-term projects.

What are the key skills and qualifications needed to thrive as a contract data engineer?

To thrive as a Contract Data Engineer, you need strong proficiency in data modeling, ETL processes, and programming languages such as Python or SQL, often supported by a degree in computer science or a related field. Familiarity with big data platforms (e.g., Hadoop, Spark), cloud services (AWS, Azure, GCP), and relevant certifications like Google Cloud Professional Data Engineer are typically required. Excellent problem-solving, adaptability, and effective communication are crucial soft skills in this role. These competencies enable efficient project delivery, seamless collaboration with stakeholders, and the ability to quickly adapt to new technical environments and client requirements.

What are some common challenges faced by contract data engineers and how can they be addressed?

Contract data engineers often face the challenge of quickly familiarizing themselves with a company's existing data infrastructure and processes. Since contracts are typically short-term, there is limited time to onboard, understand unique data pipelines, and build relationships with stakeholders. To address this, successful contract data engineers proactively communicate with team members, document their work thoroughly, and leverage their prior experience with a variety of tools and platforms. Flexibility and strong problem-solving skills are essential for adapting to new environments and delivering results efficiently.

What is the difference between Contract Data Engineering vs Data Analyst?

AspectContract Data EngineeringData Analyst
Required SkillsSQL, Python, ETL, cloud platforms, data pipeline developmentSQL, Excel, data visualization, reporting tools
Work EnvironmentProject-based, technical teams, cloud or on-premises infrastructureBusiness units, reporting teams, often in office or remote
Industry UsageTech, finance, healthcare, retailMarketing, finance, healthcare, retail

Contract Data Engineers focus on building and maintaining data pipelines and infrastructure, requiring technical skills in programming and cloud platforms. Data Analysts interpret data, create reports, and visualize insights, often using different tools. While both roles work with data, Contract Data Engineering is more technical and infrastructure-oriented, whereas Data Analysts focus on data interpretation and business insights.

What are the most commonly searched types of Data Engineering jobs in Berkeley, CA?

The most popular types of Data Engineering jobs in Berkeley, CA are:

What are popular job titles related to Contract Data Engineering jobs in Berkeley, CA?

For Contract Data Engineering jobs in Berkeley, CA, the most frequently searched job titles are:

What job categories do people searching Contract Data Engineering jobs in Berkeley, CA look for?

The top searched job categories for Contract Data Engineering jobs in Berkeley, CA are:

What cities near Berkeley, CA are hiring for Contract Data Engineering jobs?

Cities near Berkeley, CA with the most Contract Data Engineering job openings:

Contract Data Engineering jobs near you

Data Engineer - AI Model Evaluation

Mercor

San Francisco, CA • Remote

$80/hr

Full-time

Posted 9 days ago

Job description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: Data Engineer (Coding Agent Experience)
Type: Contract
Compensation: $80/hour
Location: Remote

Role Responsibilities

  • Use frontier AI coding agents to complete and evaluate complex data engineering tasks.
  • Review model-generated implementations involving ETL pipelines, data warehouses, analytics platforms, and distributed data systems.
  • Identify bugs, edge cases, scalability issues, and failure modes in model outputs.
  • Compare outputs from multiple frontier models and assess their strengths and weaknesses.
  • Apply professional engineering judgment to realistic data engineering scenarios.

Qualifications

Must-Have

  • 2+ years of professional data engineering experience.
  • Experience building ETL pipelines, data warehouses, analytics platforms, or distributed data systems.
  • Regular use of AI coding agents such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or similar tools.
  • Ability to evaluate model-generated data infrastructure and pipeline implementations.

Preferred

  • Experience operating large-scale data platforms.

Compensation & Legal

  • $400 per accepted task.
  • Compensation is tied to accepted work.

Application Process (Takes 20–30 mins to complete)

  • Upload resume
  • AI interview based on your resume
  • Submit form

Resources & Support

  • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
  • For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.