AI-Ready Data Governance Lead

dv01

New York (NY)

On-site

USD 190,000 - 220,000

Full time

14 days+

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Benefits offered by this job

Unlimited PTO
Learning & Development fund
Remote-first environment
Health care and financial planning
Fitness/Wellness stipend

Job summary

dv01 is seeking a Data Governance Lead to define ownership across data domains, build a comprehensive quality framework, and enforce metadata and access controls for AI-enabled analytics. You will collaborate with Data Product, Engineering, and Legal to ensure trusted, scalable data foundations.

You will replace ad-hoc governance with deliberate programs, track commitments, and drive measurable improvements in data quality while working across teams to formalize definitions and lineage.

Qualifications

  • 7+ years of experience in data governance, data quality, or data management.
  • Proven ability to build programs from the ground up.
  • Meticulous and exceptionally organized; identifies and fixes data definitions.
  • Fluent in technical conversations; can review SQL and data models.

Responsibilities

  • Own the data quality framework and its metrics across loan-level and deal-level data.
  • Establish ownership and stewardship for each data domain.
  • Own the data dictionary and business definitions across systems.
  • Own data rights and enforceability within the platform.
  • Run data governance like a program with clear goals and persistence.

Skills

Data governance
Data quality
Data management
BigQuery
dbt
Unity Catalog
Collibra
Alation
SQL
AI governance

Tools

BigQuery
dbt
Unity Catalog
Collibra
Alation

Job description

dv01 is seeking a Data Governance Lead to define ownership across data domains, build a comprehensive quality framework, and enforce metadata and access controls for AI-enabled analytics. You will collaborate with Data Product, Engineering, and Legal to ensure trusted, scalable data foundations.

You will replace ad-hoc governance with deliberate programs, track commitments, and drive measurable improvements in data quality while working across teams to formalize definitions and lineage.

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