Senior Data Quality Steward for Prime Product Data

Caterpillar Inc.; Chicago (IL); On-site; USD 108,000 - 169,000; Full time

Benefits offered by this job

Medical, dental, and vision

401(k) plan

Paid time off

Career development

Incentive bonus

Job summary

Caterpillar Inc. in Chicago, IL is seeking a Product Data Steward to bring a data science and analytics lens to Prime and Parts attribute data at scale, using automated methods to identify and resolve critical exceptions.

You will profile data with SQL and Python, design dashboards to surface data health trends, and define content standards while partnering with Data Quality Engineering to extend profiling across product domains.

Qualifications

• Experience in data quality engineering or analytics.
• Proficiency in SQL and Python for profiling and automation.
• Experience building dashboards (Power BI/Tableau).
• Familiarity with PIM/MDM platforms such as Akeneo.

Responsibilities

• Build and maintain data quality scorecards for Prime attributes.
• Profile Prime product data with SQL/Python and quantify impact.
• Design dashboards to surface data health trends for stakeholders.
• Apply automated rules to triage data quality issues.
• Collaborate with Data Quality Engineering for reusable logic.
• Define and refine Prime content standards and business rules.
• Support enrichment and migration validation with quantitative measures.
• Communicate findings clearly to technical and non-technical audiences.

Skills

SQL

Python

Data profiling

Data quality

Dashboards

Education

Bachelor's in Data Science

Tools

Power BI

Tableau

Akeneo

Job description

Caterpillar Inc. in Chicago, IL is seeking a Product Data Steward to bring a data science and analytics lens to Prime and Parts attribute data at scale, using automated methods to identify and resolve critical exceptions.

You will profile data with SQL and Python, design dashboards to surface data health trends, and define content standards while partnering with Data Quality Engineering to extend profiling across product domains.