Data Quality Product Owner
denver, CO
Job Title: Data Quality Product Owner
Location-Type: Fully Remote (US)
Start Date Is: ASAP
Duration: 6-month Contract-to-Hire
Compensation Range: $48.71/hr – $55/hr
Job Description:
Own and operate enterprise data quality capabilities as a product, ensuring trusted, reliable data across operational systems, analytics platforms, and AI pipelines.
Day-to-Day Responsibilities:
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Own the enterprise data quality roadmap, backlog, and delivery aligned to governance priorities
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Translate business, analytics, and AI requirements into data quality rules and monitoring
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Configure and operate Monte Carlo for data observability (freshness, volume, schema, anomalies)
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Oversee day-to-day data quality operations including alert triage and root cause analysis
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Establish data quality standards for critical data elements, reporting, KPIs, and dashboards
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Partner with data engineering, analytics, and data science teams on remediation and prevention
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Lead and mentor Data Quality Engineers and communicate quality health to stakeholders
Requirements:
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Must-Haves:
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7 years in data, analytics, or data management with a strong focus on data quality
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3 years of people leadership supporting data or analytics platforms
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Hands-on experience with Monte Carlo or similar data observability tools
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Strong understanding of data quality dimensions across operational, analytical, and AI use cases
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Experience with modern data platforms (cloud data warehouses/lakehouses, ETL/ELT, BI tools)
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Nice-to-Haves:
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Experience within a formal Data Governance organization
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Familiarity with data observability, anomaly detection, and data drift
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Experience supporting AI/ML or advanced analytics use cases
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Background in regulated industries
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For Managers:
This role fulfills the need to establish and scale enterprise-wide data quality as a governed, product-driven capability. The ideal candidate blends hands-on data observability expertise with strong product ownership and people leadership, ensuring data can be trusted across analytics and AI initiatives.
LinkedIn Boolean String: ("data quality” OR "data observability”) AND Monte Carlo AND (product owner OR product manager) AND (data governance OR analytics)
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