Lead Data Governance Engineer

Global Payments Inc. • Cincinnati, OH

1d

About The Position

The Lead Data Governance Engineer will join the Data Products team to help ensure that data used in analytical, decisioning, optimization, and commercial products is accurate, complete, well understood, and fit for purpose. The role assesses data quality against product requirements and business criticality, establishes acceptance criteria and thresholds, and builds repeatable profiling, reconciliation, and monitoring controls for critical datasets.

The position investigates complex data anomalies across source systems, ingestion, transformation, business logic, and downstream consumption, partnering with accountable teams on remediation. It defines semantic expectations, data contracts, automated alerts, and tolerances for critical product inputs, and documents definitions, dependencies, assumptions, limitations, and appropriate uses. The engineer communicates data risks and their potential product, operational, business, and client impact to technical and non-technical stakeholders, and recommends systemic improvements to reduce recurring issues.

The role works across Product, Data Engineering, Data Science, Data Governance, and business subject-matter experts to embed data assurance throughout the product development lifecycle.

Requirements

• Bachelor’s degree in Computer Science, Statistics, Mathematics, Information Systems, Engineering, or a related field.
• 10+ years of experience in data analytics, data quality, data engineering, or a related discipline.
• Ability to operate independently as a senior individual contributor.
• Advanced SQL skills.
• Demonstrated success profiling, reconciling, and investigating large, complex datasets.
• Experience defining data-quality rules, thresholds, controls, and monitoring, including anomaly investigation and root-cause analysis.
• Strong written and verbal communication skills.
• Ability to translate technical data issues into clear product, business, operational, and client implications.

Nice To Haves

• Experience in merchant acquiring, a payment service provider, or a card network environment.
• Experience supporting data-intensive products such as transaction processing, optimization, real-time recommendation systems, or commercial data products.
• Familiarity with cloud data platforms and modern data architectures, including Snowflake, Databricks, and AWS.
• Familiarity with data contracts or data-product operating models.

Responsibilities

• Assess the quality and fitness for purpose of data used in new and existing products.
• Establish data acceptance criteria and thresholds based on product requirements and business criticality.
• Build repeatable profiling, reconciliation, and monitoring controls across critical datasets, including measures such as fill rates, null rates, volumes, ranges, distributions, and schema changes.
• Investigate complex data anomalies and discrepancies, identify root causes across source systems, ingestion, transformation, business logic, and downstream consumption, and partner with accountable teams on remediation.
• Define semantic expectations, data contracts, automated alerts, and tolerances for critical product inputs.
• Document data definitions, dependencies, assumptions, limitations, and appropriate uses.
• Communicate data risks and potential product, operational, business, and client impacts to technical and non-technical stakeholders.
• Recommend systemic improvements that reduce recurring data issues.
• Collaborate with Product, Data Engineering, Data Science, Data Governance, and business subject-matter experts to embed data assurance throughout product development.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior