Lead Data Governance Engineer

Global Payment Holding Company • Cincinnati, OH

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About The Position

The Lead Data Governance Engineer will 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 for new and existing products, establishes acceptance criteria, and builds repeatable controls to profile, reconcile, and monitor critical datasets. It investigates complex data anomalies and communicates data risks and their potential impacts to stakeholders.

The engineer works across Product, Data Engineering, Data Science, Data Governance, and business subject-matter experts to embed data assurance throughout the product development lifecycle. This is a senior individual-contributor role requiring independent work and collaboration with teams accountable for data remediation and product outcomes.

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 and 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, including the 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, as well as data contracts or data-product operating models.

Responsibilities

• Assess the quality and fitness for purpose of data used in new and existing products, and establish 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 definitions, dependencies, assumptions, limitations, and appropriate uses.
• Communicate data risks and potential product, operational, business, and client impacts to technical and non-technical stakeholders, and recommend systemic improvements to reduce recurring issues.
• Work across Product, Data Engineering, Data Science, Data Governance, and business subject-matter experts to embed data assurance throughout the product development lifecycle.

What This Job Offers

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