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Rig Data Jobs in California (NOW HIRING)

You'll design and own an automated test rig, a rack of devices wired into our CI/CD pipeline that ... Run long-duration audio session testing (multi-hour, synthetic data) and battery/thermal ...

Establish ground-to-flight correlation methodology: characterize offload rig artifacts, derive ... Feed deployment test data into the integrated structural model; participate in model-test ...

Establish ground-to-flight correlation methodology: characterize offload rig artifacts, derive ... Feed deployment test data into the integrated structural model; participate in model-test ...

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Rig Data information

See California salary details

$35

$66

$83

How much do rig data jobs pay per hour?

As of Sep 8, 2026, the average hourly pay for rig data in California is $66.72, according to ZipRecruiter salary data. Most workers in this role earn between $59.09 and $75.67 per hour, depending on experience, location, and employer.

What is a rig data?

A Rig Data job involves collecting, managing, and analyzing data related to drilling operations on oil and gas rigs. Professionals in this role monitor real-time data from sensors to track drilling performance, safety metrics, and operational efficiency. They work closely with engineers and drilling teams to ensure accurate data reporting and help optimize drilling processes. Strong technical skills, attention to detail, and familiarity with industry software are essential for success in this role.

What does a rig data do?

A typical day for a Rig Data specialist involves monitoring drilling activities, collecting and validating real-time data from the rig, and preparing detailed reports for operations teams and management. You will frequently interact with drilling engineers, rig supervisors, and geologists to ensure data accuracy and address operational concerns. The role often requires working on a rotational schedule, sometimes onsite at remote rig locations, which demands adaptability and a strong commitment to safety protocols. Despite the challenges, the position offers valuable insight into drilling operations and serves as a strong foundation for career advancement within the oil and gas industry.

What are the key skills and qualifications needed to thrive in the rig data position, and why are they important?

To thrive as a Rig Data specialist, you need a solid understanding of drilling operations, data management, and analytical skills, often supported by a background in petroleum engineering, geology, or a related field. Familiarity with industry-standard software such as WellView, OpenWells, or RigSense, and sometimes certifications like Well Control (IWCF/IADC), are commonly required. Strong attention to detail, effective communication, and the ability to work efficiently in high-pressure environments set exceptional candidates apart. These skills and qualities are crucial for accurate data collection, timely reporting, and supporting the safe and efficient operation of drilling projects.

What are popular job titles related to Rig Data jobs in California?

For Rig Data jobs in California, the most frequently searched job titles are:

Infographic showing various Rig Data job openings in California as of August 2026, with employment types broken down into 91% Full Time, and 9% Part Time. Highlights an 100% In-person job distribution, with an average salary of $138,779 per year, or $66.7 per hour.

Strategic Projects Lead

Foundry Robotics Inc

San Francisco, CA โ€ข On-site

Full-time

Medical, Dental, Vision, PTO

Re-posted 17 days ago


Key responsibilities

  • Manage the rig fleet end-to-end, including procurement, lifecycle, asset tracking, spares, and vendor relationships

  • Define success criteria with the model team, translate data needs into rejection rules, and run post-capture QA and validation

  • Own new task ramp-up, including specification, SOP creation, pilot batch design, and quality gate sign-off


Job description

About Us
Foundry Robotics is building an AI-native robotics manufacturing company focused on deploying advanced assembly and production capability for leading robotics companies and national-security-critical hardware. Basically, we're building robots that build robots.
We are reimagining manufacturing through advanced robotics. Our mission is to rebuild the American manufacturing industry as an AI-first, assembly-focused, dual-use contract manufacturer. We aim to empower manufacturers with intelligent, efficient, and adaptable robotic systems that redefine productivity and quality.
The Role
This role is for a Strategic Project Lead who thrives on turning model team requirements into production data, equally comfortable architecting QA systems from first principles and calibrating a rig on the floor. You will define what gets captured, how it lands, and whether it is usable, from early task spec through pre-delivery validation. You will stand up the data collection program from scratch and drive rapid build-test-learn cycles to deliver a dataset that is both rigorous and scalable.
You will be the day-to-day interface with our model team and the frontier labs we deliver to, and the source of truth for hours collected, hours delivered, and hours usable. You will partner closely with the Operations Manager, Robotics Data, who owns the workforce, floor execution, and daily fleet readiness.
Key Responsibilities
  • Manage the rig fleet end-to-end (UMI grippers, GoPros, VR headsets and controllers), including procurement, lifecycle, asset tracking, spares, and vendor relationships
  • Own rig calibration cadence and drift detection, including GoPro intrinsics, fisheye calibration, UMI gripper width drift, and per-operator VR eye-tracking calibration
  • Define success criteria with the model team, translating high-level data needs into rejection rules an assembler can apply consistently
  • Author SOPs and hand them to the Operations Manager for floor execution
  • Own new task ramp-up, including spec, SOP, pilot batch design, and quality gate sign-off before full production
  • Curate gold-standard demos (20-50 reference demos per task), maintained against drift
  • Run post-capture QA (sampling + success classifier) and pre-delivery validation against model team spec
  • Track diversity and coverage across task variants, object positions, lighting conditions, and operator styles
  • Run daily capture logs and weekly dataset reporting to model and research stakeholders, including hours captured, hours usable, mix vs. target, top rejection reasons, and blockers
  • Own task spec versioning, coordinating SOP updates, retraining triggers, and data v1/v2 marking when the model team changes a spec
  • Own the 48-hour handoff SLA, including staging, upload integrity, episode schema enforcement, and metadata completeness (operator ID, task ID, success label, timestamp written atomically)
  • Run RCA when batches get rejected and close the loop with the floor
  • Define and report against program-level OKRs for usable hours delivered, mix accuracy, and SLA attainment
  • Own data governance and compliance, including episode-level metadata for auditability, retention and deletion policies, and adherence to data handling standards required by frontier lab partners
What We're Looking For
  • 3-5 years as a strong PM or TPM with exposure to hardware, data pipelines, or physical workflows
  • Proven ability to build data collection or technical operations programs from the ground up and improve on existing ones
  • Comfortable owning task specs, QA programs, and standardization
  • Equally effective at a desk and on the floor, with deep hands-on experience calibrating a rig one hour and writing a stakeholder update the next
  • SQL or Python proficient enough to pull your own data and build your own dashboards
  • Track record tracking and improving program metrics (usable hours, mix accuracy, SLA attainment, rejection rates)
  • Experience providing technical input in a cross-functional environment with researchers and engineers
  • Collaborative by nature, you consider downstream impacts on operators, model teams, and infrastructure when making program decisions
  • Bias toward action, scrappy problem solving, and moving fast without sacrificing rigor
Nice to Have (Not Required)
  • Experience supporting vendor or hardware supplier relationships
  • Exposure to robotics, VLA models, or foundation model training data
  • Experience scaling a data collection program from prototype to high-volume production
  • Familiarity with computer vision, sensor calibration, or robotics data pipelines
Why Join Us?
This is one of the only places where world-class manufacturing operators, mechanical engineers, robotics researchers, and software engineers sit in the same room - building production systems together.
We are committed to being deeply embedded in the U.S. industrial base. Our focus is simple: build adaptive robotic assembly systems that make American manufacturing scalable, resilient, and competitive again.
If you want to run a mature, well-defined commercial org, this may not be the role.
If you want to build the commercial engine that brings AI-driven manufacturing to every industrial and energy customer in America - this is it.
The base salary range for this full-time position in the location of San Francisco is:
$150,000-$250,000 USD
Compensation packages at Foundry Robotics for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Foundry Robotics employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. You'll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, and generous PTO.