Data Governance Associate

HIGH BRIDGE CONSULTING LLCNew York, NY
$60 - $80Hybrid

About The Position

Our client is a leading global independent investment banking advisory firm providing strategic advice to corporations, institutions, and governments. The firm also offers wealth management, equities, and investment management services across major markets. Seeking a Data Governance Associate to support day-to-day data governance activities, working closely with business stakeholders and technical teams to maintain accurate, trusted, and well-defined data across enterprise platforms. This role will help drive data quality, governance documentation, issue resolution, and data standards across key business domains.

Requirements

  • 3–6 years of experience in data governance, data management, business analysis, or similar roles
  • Strong understanding of data governance, data quality, stewardship, and issue management
  • SQL skills for data analysis, issue investigation, and validation
  • Python experience for automation, data cleansing, profiling, and validation
  • Experience working with tools such as Databricks, Jupyter, Excel, or BI platforms
  • Strong communication, organization, and stakeholder management skills

Nice To Haves

  • Exposure to CRM or deal management systems such as DealCloud or Salesforce is a plus
  • Financial services, consulting, or other data-intensive industry experience preferred

Responsibilities

  • Support data governance processes across business and technology teams
  • Build and maintain Python notebooks for data matching, survivorship, and reconciliation
  • Document business definitions, glossaries, and data domains
  • Track data issues, coordinate resolutions, and maintain issue logs
  • Help define data standards, validation rules, and required fields
  • Partner with architects and project teams to align data models with governed definitions
  • Support data quality rules, monitoring, dashboards, and reporting
  • Maintain governance documentation, training materials, and communications
  • Define and prioritize data quality metrics across key data domains
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