Senior Data Governance & Architecture Lead (Remote)

VIVA USA Inc; Raleigh (NC); Hybrid; USD 120,000 - 160,000; Full time

Job summary

VIVA USA Inc. in Raleigh, NC is seeking a Senior Data Scientist contractor to lead enterprise data strategy and governance initiatives across analytics platforms and Azure-based data tools.

The role focuses on establishing consistent data practices, metadata, lineage, and data quality with business and technical teams. The ideal candidate will shape organization-wide data management practices, collaborate with data owners, and drive scalable, reusable data patterns in support of rapid enterprise

Qualifications

• Experience establishing enterprise data elements, lineage, and business rules across units.
• Ability to translate data needs into consistent enterprise standards with business teams.
• Proven track record implementing metadata, data quality, and lineage practices across projects.

Responsibilities

• Partner with stakeholders to understand data needs and identify improvement opportunities.
• Identify authoritative data sources and establish common business definitions.
• Incorporate governance, metadata, lineage, and data quality into ongoing initiatives.
• Standardize data ingestion, transformation, cleansing, and validation patterns using Azure tools.
• Maintain an inventory of data assets, owners, stewards, and system relationships.
• Document data flows across applications and platforms.
• Contribute to data architecture discussions for consistency and reuse.

Skills

Enterprise data strategy

Governance

Data architecture

Stakeholder collaboration

Tools

Azure Data Factory

Azure Databricks

Power BI

Job description

VIVA USA Inc. in Raleigh, NC is seeking a Senior Data Scientist contractor to lead enterprise data strategy and governance initiatives across analytics platforms and Azure-based data tools.

The role focuses on establishing consistent data practices, metadata, lineage, and data quality with business and technical teams. The ideal candidate will shape organization-wide data management practices, collaborate with data owners, and drive scalable, reusable data patterns in support of rapid enterprise