Data Operations Lead

Bedrock Robotics•San Francisco, CA

12h

About The Position

Bedrock Robotics is seeking a Data Operations Lead to own ongoing data collection support for its fleet. The role ensures machines in the field reliably produce, retain, and deliver terabyte-scale daily data volumes that Engineering depends on. As the company scales its machine count, partners, and sites and introduces new machine types and a next-generation platform, this person will define data collection strategies and oversee execution, including decisions about what and when to collect and the data center strategy for efficient uploads. This is a field-forward leadership role responsible for building the organization and operating systems that keep data flowing efficiently and economically. The Data Operations Lead will establish service-level agreements, methods, monitoring, and infrastructure needs; own field-side data pipeline reliability; and work across Engineering, Product, Infrastructure, IT, and Data teams to improve tooling and reduce manual effort. The role also leads organizational design, labor strategy, hiring and development for data technicians and couriers, and performance management of third-party partners. The position involves regular presence at active job sites, dealer and upfit facilities, and Bedrock offices, with approximately 30% travel, concentrated around site and data center bring-ups and service partner engagements.

Requirements

8–10 years of experience in operations, field deployment, or program leadership, including 3+ years working with distributed teams across multiple sites or regions.
Experience working with non-exempt employees and either directly managing non-exempt employees or overseeing contingent staff.
Track record of owning operational metrics for a physical fleet at scale, including SLA design and vendor performance management.
Experience running operations for a customer-facing product against committed SLAs, or an equivalent paid-service operation.
Experience partnering with Engineering or Product as the operational voice in platform and roadmap decisions.
Comfort working in an early-stage environment where processes are being established, combined with the discipline to document them.
Strong written and verbal communication skills with customer executives, dealer partners, and internal leadership.
Willingness to travel approximately 30% to job sites, dealer facilities, and partner locations.

Nice To Haves

Background in autonomy, machine control, telematics, or connected fleet solutions.
Experience operating a data collection fleet or equivalent field data infrastructure.
Experience structuring in-house versus third-party service decisions and the related contractual and performance frameworks.
Established relationships with large general contractors, hyperscaler builders, or heavy civil customers.
Understanding of data center requirements for data offload.
Experience working through a platform generation transition and/or introducing new machine or equipment types.

Responsibilities

Own ongoing fleet data collection support, ensuring machines reliably produce, retain, and deliver the data Engineering needs.
Own field operations for Autonomous and Bedrock Intelligence machines to meet customer and engineering product standards, including monitoring, response, and data completeness expectations.
Own field operations for Data Collection machines and define efficient collection methods that provide engineers with critical model-development data.
Manage data yield as an operational metric alongside machine uptime, including identifying factors behind gaps in usable, complete, correctly labeled data.
Work with Engineering and Product to prioritize and address data loss in the pipeline.
Build an economical data service by defining clear SLAs, understanding costs, running simulations of network strategy and SLA trade-offs, and optimizing operations.
Own field-side reliability of pipeline offload, connectivity, storage, and handoff, along with an operating cadence that detects degradation early.
Translate Engineering, ML, and Bedrock Intelligence product requirements into field-executable standards and communicate field constraints back to internal teams.
Partner with Infrastructure, Product, Engineering, and Data teams on tooling, instrumentation, and a roadmap to reduce manual effort as the fleet grows.
Work with IT to define data center needs for efficient data uploads and develop the playbook for bringing new data centers online for data offload.
Define labor and third-party strategies for data collection.
Monitor and continuously improve operational performance.
Own data operations organizational design, labor strategies, and hiring and development for data technicians and couriers.
Build relationships with third-party service partners and oversee their performance against specifications.
Bridge active field operations and internal engineering teams that use the data.
Build customer relationships as needed and ensure Bedrock employees and representatives comply with active site rules and requirements.