AI Data Quality & Governance Lead

TEKsystems; Newark (NJ); Hybrid; USD 7,577,000 - 8,954,000; Full time

Benefits offered by this job

Medical, dental & vision

401(k) Retirement Plan

Health Spending Account (HSA)

Transportation benefits

Job summary

TEKsystems seeks a senior specialist to drive data quality, governance, and Responsible AI controls in Newark, NJ. The role embeds controls into data sourcing, pipelines, metadata, and AI lifecycle gates to deliver audit-ready evidence.

Partner with data architects, engineering, platform, security, and risk teams to define DQ rules, thresholds, and reusable control patterns across data products and AI use cases. Hybrid work in Newark.

Qualifications

• Extensive experience in data quality, governance, and AI governance.
• Experience embedding controls into data pipelines and CI/CD processes.
• Strong communication and leadership for cross-functional teams.

Responsibilities

• Lead enterprise implementation of data quality and AI data readiness controls across data sources and AI use cases.
• Define AI-ready data in practice with thresholds, lineage, and metadata requirements.
• Translate control requirements into measurable rules embedded in pipelines and dashboards.
• Collaborate with data architects, engineers, platform teams, and risk/compliance.

Skills

Data quality

Data governance

Responsible AI

Data management

Control operations

Data architecture

Communication

Leadership

Education

Bachelor's degree in computer science, data science, engineering, information systems, risk management, or related field

Tools

Ataccama

Informatica Data Quality

Collibra Data Quality

Soda

Monte Carlo

Great Expectations

OpenLineage

Jira

Power BI

Job description

TEKsystems seeks a senior specialist to drive data quality, governance, and Responsible AI controls in Newark, NJ. The role embeds controls into data sourcing, pipelines, metadata, and AI lifecycle gates to deliver audit-ready evidence.

Partner with data architects, engineering, platform, security, and risk teams to define DQ rules, thresholds, and reusable control patterns across data products and AI use cases. Hybrid work in Newark.