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Data Collection Engineer Jobs (NOW HIRING)

Hark

Data Collection

San Jose, CA · On-site

$150K - $250K/yr

You'll work directly with researchers, engineers, and external partners, and the data you deliver ... Design and run data collection programs end-to-end - scoping requirements, writing instructions ...

Hark

Data Collection

San Jose, CA

$150K - $250K/yr

You'll work directly with researchers, engineers, and external partners, and the data you deliver ... Design and run data collection programs end-to-end - scoping requirements, writing instructions ...

ALTEN

Data Collection Operator

San Francisco, CA · On-site

$30/hr

We're ALTEN Technology USA, an engineering company helping clients bring groundbreaking ideas to ... Experience with data collection or annotations Compensation Range: * $30/hour * The actual salary ...

Aerotek

Data Collection Specialist

San Francisco, CA · On-site

$25 - $30/hr

Interest in robotics, AI, or engineering * Prior data collection or lab experience is a plus Why Apply? * ⚡ Work with advanced robotics and AI tech * 📈 Fast-track your career in a growing field ...

Aerotek

Data Collection Specialist

San Francisco, CA

$25 - $30/hr

Interest in robotics, AI, or engineering * Prior data collection or lab experience is a plus Why Apply? * ⚡ Work with advanced robotics and AI tech * 📈 Fast-track your career in a growing field ...

Tesla

Data Collection Operator, Optimus

Palo Alto, CA · On-site

The primary objectives of this role are to collect data, assist with engineering operations, and report equipment feedback. Responsibilities : • Perform data collection tasks such as manipulation ...

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Data Collection Engineer information

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$51.5K

$147.5K

$197K

How much do data collection engineer jobs pay per year?

As of Jun 4, 2026, the average yearly pay for data collection engineer in the United States is $147,461.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,000.00 and $196,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Collection Engineer, and why are they important?

To thrive as a Data Collection Engineer, you need a solid background in computer science or engineering, experience with data acquisition, and proficiency in programming languages like Python or Java. Familiarity with data collection frameworks, APIs, sensor technologies, and cloud platforms is commonly required, along with certifications in data engineering or related fields. Strong analytical thinking, problem-solving abilities, and effective communication are crucial soft skills for collaborating with cross-functional teams and troubleshooting issues. These skills and qualities are important to ensure accurate, reliable, and scalable data pipelines that support critical business analytics and decision-making.

What are some common challenges Data Collection Engineers face when gathering and managing large-scale datasets?

Data Collection Engineers frequently encounter challenges such as ensuring data quality and consistency across various sources, managing the volume and velocity of incoming data, and handling data privacy or compliance concerns. They must also design robust pipelines that can scale as data needs grow, and often collaborate with data scientists, software engineers, and product teams to align data collection strategies with project goals. Regularly troubleshooting data ingestion errors and adapting to changing data requirements are also key parts of the role.

What are Data Collection Engineers?

Data Collection Engineers are professionals who design, implement, and maintain systems for gathering data from various sources. Their work involves creating pipelines to collect, store, and preprocess data, often in support of analytics, machine learning, or business intelligence projects. They work closely with data scientists and software engineers to ensure data quality and reliability. Data Collection Engineers may use a range of tools and technologies, such as APIs, web scraping frameworks, and database management systems, to automate and optimize data acquisition processes.

What is the difference between Data Collection Engineer vs Data Analyst?

AspectData Collection EngineerData Analyst
Primary FocusDesigning and implementing data collection systems and pipelinesAnalyzing and interpreting data to support business decisions
Skills & CertificationsData engineering, SQL, programming (Python, Java), data architectureStatistical analysis, data visualization, SQL, Excel
Work EnvironmentData engineering teams, IT infrastructure, cloud platformsBusiness units, analytics teams, reporting tools

While Data Collection Engineers focus on building and maintaining data pipelines and infrastructure, Data Analysts interpret the collected data to generate insights. Both roles often collaborate but serve different stages of the data lifecycle, with the engineer ensuring data availability and the analyst deriving actionable insights.

More about Data Collection Engineer jobs
What states have the most Data Collection Engineer jobs? States with the most job openings for Data Collection Engineer jobs include:
What job categories do people searching Data Collection Engineer jobs look for? The top searched job categories for Data Collection Engineer jobs are:
Data Collection Engineer jobs near you
Infographic showing various Data Collection Engineer job openings in the United States as of May 2026, with employment types broken down into 72% Full Time, 14% Part Time, and 14% Contract. Highlights an 100% In-person job distribution, with an average salary of $147,461 per year, or $70.9 per hour.

Robotics Data Collection Engineer

Nastech Global

Warren, MI • On-site

Contractor

Posted 4 days ago

Job description

Position: Robotics Data Collection Engineer

Location: Warren, Michigan (Onsite)

Duration: 12+Months with possible extensions

Main Skills: Senior Robotics Data Collection Engineer (MLE, Python, Cloud exp, Linux)

Position Summary:

Join Automation, Robotics & Controls (ARC) AI team as a Robotics Data Collection Engineer. In this hands-on role, you will work directly with advanced robotic systems to collect, organize, and validate training data that enables AI-powered robotic manipulation in automotive manufacturing. You will contribute to building the datasets that power the next generation of intelligent manufacturing automation at Warren Technical Center.

Key Responsibilities:

  • Collect high-quality robot telemetry, sensor, and visual data from manufacturing robotic systems in lab and production-like environments.
  • Operate and monitor robotic systems, GELLO teleop interfaces, and data collection hardware.
  • Organize, label, and validate data according to established annotation guidelines and quality standards.
  • Perform manual annotation and verification when necessary to generate high-quality ground truth labels.
  • Execute data collection campaigns following documented protocols and experimental designs.
  • Troubleshoot data collection issues and document problems for engineering teams.
  • Collaborate with AI engineers, robotics engineers, and manufacturing teams to ensure data meets model training requirements.

Required Qualifications:

  • College or bachelor’s degree in engineering (Mechanical Engineering or Electrical Engineering preferred).
  • Ability to work on-site at Warren Technical Center, 5 days per week.
  • Attention to detail and ability to follow technical procedures and documentation.
  • Reliability, accountability, and ability to work independently and as part of a team.
  • Strong, demonstrated hands-on experience operating, troubleshooting, and maintaining industrial or collaborative robotic arms.
  • Proficiency in Linux environments and basic scripting (e.g., Python) to interface with robotic systems and manage data pipelines.
  • Proven experience working directly with perception sensors and hardware, with a solid understanding of capturing and validating high-quality sensor data.

Preferred Qualifications:

  • Experience with robotics, manufacturing, or data collection.
  • Familiarity with Python, Linux, or data tools (beneficial but not required).
  • Experience operating or troubleshooting technical equipment.
  • Basic understanding of machine learning, AI, or data annotation concepts.
  • Experience in automotive or manufacturing environments.

What is Offered:

•              Hands-on experience with cutting-edge robotics and AI technology.

•              Opportunity to contribute to transformative manufacturing automation.

•              Collaborative team environment with world-class engineers and researchers.