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Best fit for a senior or lead practitioner who has owned data quality for multi-party or partner pipelines, can influence without pure authority, and is willing to work on-site in San Jose. Thin public company context in the provided sources; weight the posted title and local setup when deciding fit.
As Lead, Data Quality – Partnerships at Figure in San Jose, you would set quality standards for partner-facing datasets, define rules and SLAs with partnership and data engineering teams, triage defects, and drive root-cause fixes. A typical day mixes metric reviews, partner data issue triage, playbook updates, and stakeholder syncs on trust, completeness, and freshness.
Useful focus areas for this title: data profiling and anomaly detection, data contracts and SLAs, SQL and pipeline observability, stakeholder communication with partnerships teams, and incident/RCA discipline. No certification list or costs were provided for this posting.
No. The listing marks remote as off and places the job in San Jose, CA.
You likely own quality for data exchanged with or about partners—SLAs, issue triage, and cross-team standards—not only internal warehouse hygiene.
No salary bands, star ratings, or employer-review scores were supplied for this enricher; treat those as unknown until Figure or the listing provides them.
Website: figure.com
Public cache only — not an employee review.
Figure, an AI robotics company headquartered in San Jose, CA, seeks a Lead, Data Quality - Partnerships to oversee our external data vendor ecosystem and uphold rigorous quality standards across our training operations. This full-time role places you at the center of scaling our data foundation as we develop humanoid robots capable of human-level intelligence. Role Overview The data quality infrastructure supporting our robotics systems depends on world-class annotation and review partners. In this role, you will be the senior steward of Figure's external data labeling and review vendor relationships—responsible for who we partner with, what standards they meet, and how their output maintains parity with our internal teams. You'll own the complete lifecycle of vendor management, from initial sourcing and selection through performance monitoring and offboarding. When projects transition to external vendors, you become the primary owner directing all delivery, with Project Coordinators executing the work under your oversight. Core Duties Source, evaluate, onboard, and manage a portfolio of external data labeling and review vendors. Negotiate statements of work, pricing, capacity terms, and contracts; track budgets and manage surge resources across partners. Establish and monitor service level agreements and quality acceptance criteria for every external vendor, holding them to the same standards as our in-house operations. Develop and maintain vendor performance metrics, including throughput, quality scores, inter-rater reliability, and SLA compliance tracked in regular business reviews. Design and run calibration exercises and golden set validation with vendors to ensure their output aligns with internal benchmarks. Work with engineering and ML teams to translate technical data quality requirements into clear, executable operational guidelines and specifications. Plan and coordinate vendor capacity ramps to meet project timelines, including growth into new geographic regions and burst capacity scenarios. Lead coordination between internal Project Coordinators and leadership on vendor assignments and project transitions. Who We're Looking For 6+ years of hands-on experience in data quality, labeling operations, vendor management, or ML data pipeline operations, with demonstrated end-to-end ownership of significant vendor relationships. Proven track record sourcing, contracting, and managing external data vendors; experience defining and enforcing service level agreements is essential. Strong background negotiating…
Generated for personal interview prep · 2026-07-19 UTC · getajob.ai