Reflection
Legal
DataGovernanceLead
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“Data Governance Lead at Reflection. Skills: Data governance, Data privacy, DPIAs, GDPR. Produce audit-ready data provenance records. Produce training-data summaries”
What You'll Achieve.
Satisfy auditors; Satisfy enterprise customers; Satisfy regulators; Meet EU AI Act expectations; Meet GDPR expectations; Enable timely responses to data subject requests; Enable accurate responses to data subject requests; Make audits straightforward; Make customer security reviews straightforward; Make audits fast; Make customer security reviews fast; Report residual risk on regular cadence; Help teams make confident decisions; Help teams make compliant decisions
Industry & Context.
What They're Looking For.
Must Have
5+ years in data governance, 5+ years in data privacy, Meaningful experience at a technology company, Experience handling large-scale datasets, Experience handling sensitive datasets, Hands-on experience conducting DPIAs, Hands-on experience owning DPIAs, Hands-on experience conducting privacy assessments, Hands-on experience owning privacy assessments, Hands-on experience conducting data protection documentation, Hands-on experience owning data protection documentation, Deep working knowledge of GDPR, Deep working knowledge of CCPA/CPRA, Deep working knowledge of EU AI Act, Experience with training data provenance, Experience with dataset licensing, Experience with consent management in ML/AI context, Experience building risk registers, Experience maintaining risk registers, Experience building evidence stores, Experience maintaining evidence stores, Experience building audit documentation, Experience maintaining audit documentation, Demonstrated ability to drive cross-functional alignment, Builder's mindset
Nice to Have
Experience with DPIAs reviewed by external auditors, Experience with DPIAs reviewed by regulators, Experience translating regulatory requirements into policies, Experience translating regulatory requirements into controls, Familiarity with compliance-as-code approaches, Experience with automated data validation gates, Experience with policy-enforcement pipelines, Experience with pre-deployment checks tied to data quality, Experience with pre-deployment checks tied to compliance metadata, Technical fluency with cloud data infrastructure, Technical fluency with data warehouses, Technical fluency with data cataloging tools, Technical fluency with lineage tools, Experience influencing without formal authority, Relevant certifications (CDMP), Relevant certifications (CIPP/E)
What You'll Do.
Produce audit-ready data provenance records
Produce training-data summaries
Document data quality
Own Data Protection Impact Assessments (DPIAs) end-to-end
Drive DPIAs to completion with Legal
Enforce prohibited-source controls
Enforce license controls at data intake
Maintain verified provenance log
Maintain approval log for vendor datasets
Produce lineage reports
Map model outputs to source data
Map model outputs to subject controls
Assemble evidence bundles
Maintain evidence bundles
Log data findings in risk register
Drive remediation with owners
Report residual risk to governance forums
Report residual risk to senior leadership
Partner to establish data ownership structures
Partner to establish access controls
Partner to establish stewardship practices
Champion data literacy culture
Champion responsible data use culture
Build intake checklists
How You'll Work.
Team & Collaboration
Partner with Research; Partner with Engineering; Partner with Legal; Partner with Security; Drive cross-functional alignment
Full Job Description
OUR MISSION Reflection’s mission is to build open superintelligence and make it accessible to all. We’re developing open weight models for individuals, agents, enterprises, and even nation states. Our team of AI researchers and company builders come from DeepMind, OpenAI, Google Brain, Meta, Character.AI, Anthropic and beyond. About this role - Own dataset provenance, training-data summaries, DPIAs, and the privacy and compliance posture of Reflection AI's training and evaluation data — so that every model we ship has auditable, regulator-grade evidence of its data lineage, licensing, privacy posture, and risk mitigations. What You’ll Do - Produce audit-ready data provenance records and training-data summaries for every production model — documenting origin, transformations, labeler provenance, and data quality so we can satisfy auditors, enterprise customers, and regulators on demand. - Own Data Protection Impact Assessments (DPIAs) end-to-end: drive them to completion with Legal, and publish DPIA outputs alongside model documentation to meet EU AI Act and GDPR expectations. - Enforce prohibited-source and license controls at data intake — preventing risky or non-compliant data from ever reaching a training run — and maintain a verified provenance and approval log for all vendor datasets. - Keep the company DSAR-ready by producing lineage reports that map model outputs back to source data and subject controls, enabling timely and accurate responses to data subject requests. - Assemble and maintain defensible evidence bundles — data manifests, DPIAs, consent and license records — into the enterprise evidence store so that audits and customer security reviews are straightforward and fast. - Log data findings in the risk register, drive remediation with the relevant owners, and report residual risk to governance forums and senior leadership on a regular cadence. - Partner with Research, Engineering, Legal, and Security to establish data ownership structures, access co
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