Data Governance Analyst: Data Quality & Stewardship

Teradyne; North Reading (MA); On-site; USD 117,000 - 187,000; Full time

Job summary

Teradyne is seeking a Data Governance Analyst to design, implement, and scale data governance across enterprise data domains including Customer, Supplier, and Product data. You will partner with data owners, stewards, architects, and engineers to ensure data is trusted, discoverable, and compliant, ready to support analytics, AI, and ERP systems.

The role requires hands-on experience with data platforms and tooling, strong collaboration skills, and the ability to translate business requirements

Qualifications

• 5+ years of professional experience in data governance or related data roles.
• Knowledge of data ownership, stewardship, glossaries, and metadata management.
• Hands-on with SQL, relational databases, data pipelines, ETL/ELT, and cloud platforms.
• Ability to translate business requirements into governance solutions.

Responsibilities

• Lead implementation of enterprise data governance standards across core domains.
• Develop data quality checks, rules, monitoring, metadata, and lineage.
• Collaborate with Data Owners, Stewards, architects, and engineers to define rules.
• Build and configure governance, quality, and catalog tools within pipelines and ERP.
• Support remediation of data quality issues and governance onboarding.
• Partner with cross-functional teams to improve governance operating model.

Skills

SQL & Relational DBs

Data Governance Concepts

Data Quality & Metadata

Data Pipelines/ETL

Cloud Platforms (Snowflake/AWS/Azure/G

Stakeholder Collaboration

Tools

Informatica

Collibra

Alation

Atlan

Snowflake

Azure

AWS

GCP

Job description

Teradyne is seeking a Data Governance Analyst to design, implement, and scale data governance across enterprise data domains including Customer, Supplier, and Product data. You will partner with data owners, stewards, architects, and engineers to ensure data is trusted, discoverable, and compliant, ready to support analytics, AI, and ERP systems.

The role requires hands-on experience with data platforms and tooling, strong collaboration skills, and the ability to translate business requirements