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Product Manager Data Quality and Control Jobs

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Material handler
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Canada , Guelph
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19.00 CAD / Hour
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Randstad
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Display Media Specialist
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Denmark , Copenhagen
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Better Collective
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Java/Kotlin Full Stack Software Engineer
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United States , Salt Lake City
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Software Technology Group
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Quality Assurance Automation Engineer
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United States , Salt Lake City
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Senior Database Engineer
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Poland , Gdańsk
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NAVBLUE Limited
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Database Administrator Intern
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Canada , Burlington; Toronto
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JK Contracting and Consulting Inc.
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Middle Full-Stack Web Developer
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Bulgaria , Varna
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2500.00 - 3000.00 BGN / Month
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Harbinger Marketing
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Strong-Junior Full-Stack Web Developer
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Bulgaria , Varna
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1500.00 - 2000.00 BGN / Month
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Harbinger Marketing
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Sfcc Technical Lead
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Grinteq
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United States , Las Vegas
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ASTOUND Group
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United States , Rockville
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AAC
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Senior Business Banker
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United States , River Forest
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Citi
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Citi
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India , Pune; Chennai
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Production Support - Application Support Lead
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United Kingdom , Belfast
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Robert Half
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Liquidity Risk Management Intermediate Analyst
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Philippines , Taguig
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Explore a career at the critical intersection of data strategy and business integrity with Product Manager Data Quality and Control jobs. This highly specialized and in-demand role sits at the heart of modern data-driven organizations, focusing on the governance, accuracy, and reliability of one of a company's most valuable assets: its data. Professionals in this field are strategic leaders who own the vision and roadmap for data quality frameworks and control systems, ensuring that data across the enterprise is trustworthy, consistent, and fit for purpose, thereby enabling confident decision-making and regulatory compliance. A Product Manager for Data Quality and Control typically acts as the bridge between business stakeholders, data engineers, and compliance teams. Their primary mission is to define the "why" behind data quality initiatives, championing the value of clean data throughout the organization. Common responsibilities include developing and maintaining a long-term product vision and capability roadmap for data quality tools and processes. They are responsible for creating a prioritized backlog of features and capabilities, often working within Agile or SAFe frameworks. This involves translating complex business needs and regulatory requirements into clear, actionable user stories for development teams. They lead the functional design of data quality products, which can include data profiling tools, validation rules, monitoring dashboards, and master data management systems. A key part of their role is to establish and track key performance indicators (KPIs) and Objectives and Key Results (OKRs) to measure product performance, user adoption, and the overall health of the organization's data. They facilitate collaborative sessions with senior leaders and architects to decompose large initiatives and manage stakeholder expectations, ensuring alignment with overarching enterprise goals. Typical skills and requirements for these jobs are robust. Candidates generally need several years of experience in a product management, lead product owner, or similar strategic role, preferably with a focus on data-centric products. A customer-centric mindset is crucial for understanding the pain points of data users and consumers. Strong analytical and problem-solving skills are non-negotiable, enabling them to synthesize findings from data metrics and trends to drive continuous improvement. Excellent communication and facilitation skills are essential for engaging diverse stakeholders, inspiring teams, and driving collaboration. Expertise in agile methodologies and tools like JIRA is commonly expected, and certifications such as SAFe POPM or similar are often desirable. A successful candidate will have a proven track record of making strategic prioritization decisions that maximize business value and developing products within deadlines. For those seeking a role that blends technical depth with strategic business impact, Product Manager Data Quality and Control jobs offer a challenging and rewarding career path, pivotal to building a culture of data excellence.

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