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As a Data Governance Lead, you will oversee the quality, consistency, security, integrity, and compliance of data within the context of a large Industry 4.0 Transformation Program. This role involves close collaboration with IT and OT Leaders, Architects, Business Teams, and Senior Management to ensure a culture of data excellence. You will drive the data quality function, including data profiling, cleansing, contextualization, and enrichment, to support the program’s goals and use cases.
Responsibilities:
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Lead the data quality function for the Industry 4.0 Transformation Program, focusing on data profiling, cleansing, contextualization, and enrichment.
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Collaborate with Capgemini’s Data Strategy Program to ensure a consistent approach across various initiatives and develop necessary data controls.
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Define and maintain data quality rules and metadata processes, ensuring they support critical business processes.
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Partner with global and regional data stewards, business SMEs, and data owners to develop and maintain data quality standards.
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Participate in solutioning teams, providing expertise on data management practices, tools, and procedures.
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Define replicable assets, policies, processes, standards, and patterns to accelerate delivery.
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Enforce the usage of standardized data patterns across the transformation program.
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Work with stakeholders to gather data requirements, ensuring completeness, timeliness, and accuracy.
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Ensure compliance with data protection regulations and mitigate data-related risks.
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Align data governance initiatives with business objectives through continuous collaboration with business and IT stakeholders.
Skills Required:
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Experience in data analysis, data categorization, business requirement gathering, and dashboard reporting.
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Industry experience in metal manufacturing or mining sectors.
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Advanced experience in IT/OT environments, including protocols for data exchange.
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Technical knowledge of Azure, OLTP/OLAP, SQL/NoSQL databases, Databricks, Power BI, Collibra/Informatica, SAP ECC, and HANA.
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Expertise in data contextualization, data masking, and anonymization techniques.
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Understanding of governance in ontology-oriented environments is a plus.
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Familiarity with Agile and SAFe principles.
