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Salary
≈ $22k – $59k per year (Estimated)
Location
In office (Galați)
Seniority
Middle · 3+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 6, 2026. First seen by Alion on Oct 6, 2026. Damen scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Damen is a family-owned Dutch shipbuilding group headquartered in Gorinchem, designing and building vessels such as tugs, workboats, ferries, naval and patrol ships, dredgers and offshore vessels, and providing ship repair, conversion and maritime services. Its story began in 1927 when brothers Jan and Rien Damen opened a yard in Hardinxveld, and today about 12,500 people work at more than 35 shipyards on five continents under third-generation CEO Arnout Damen. It hires commissioning, mechanical and proposal engineers, project managers, shipbuilding team leaders, mechanics and warehouse staff in the Netherlands, France, Vietnam and elsewhere.

We offer you an Ocean of Possibilities. Join our family.

About the Role

We are looking for a highly analytical and detail-oriented Data Steward to join our Business Intelligence team. In this role, you will be responsible for ensuring the accuracy, completeness, consistency, validity, and accessibility of data across assigned business domains.

As a key contributor to the organization's Data Governance framework, you will help establish and maintain data standards, monitor data quality, and support digital transformation initiatives by ensuring that business-critical information is reliable and fit for purpose. You will collaborate closely with stakeholders across all departments, as well as with the Group Data Governance community, to drive continuous improvement in data quality and management practices.

This position reports to the BI Manager

Key Responsibilities

  • Developing data quality rules and conducting periodic audits to ensure that data is fit for its intended purpose.
  • Implementing and monitoring data governance processes and policies within the assigned areas.
  • Performing data profiling and analysis activities to assess the quality, completeness, and accuracy of data assets.
  • Verifying the accuracy, completeness, and timeliness of data in the information systems used, including SAP, MES, Primavera, R-Drive, and Data Lake.
  • Defining and maintaining data standards, including naming conventions, codes, reference data, business definitions, and metadata.
  • Identifying errors in databases, analysing their root causes, and following up on their correction through to closure.
  • Configuring and monitoring data quality rules in Microsoft Purview.
  • Periodically reporting on data quality status against agreed KPIs and service levels and formulating improvement proposals.
  • Providing support to DSGa departments on data-related issues.
  • Training users on the proper use of data and applicable data standards.
  • Participating in IT projects that modify data structures and validating data migrations prior to go-live.
  • Identifying manual processes that can be automated.
  • Ensuring compliance with data confidentiality, security, and archiving requirements.

Candidate Profile

  • Bachelor’s or Master’s degree in Computer Science, Data Analytics, Software Engineering, Information Technology, Business Informatics, or a related field. Candidates with a technical engineering background (Shipbuilding, Industrial/Mechanical Engineering, Automation) and relevant experience in data management are also encouraged to apply.
  • Knowledge of Data Quality frameworks and Microsoft Purview. Professional certifications such as CDMP (DAMA), Microsoft PL-300, DP-900, SC-401, or Lean Six Sigma are considered an asset.
  • Strong understanding of Data Governance and Data Quality principles, data modeling concepts, master data structures, ERP systems (preferably SAP), advanced Microsoft Excel, basic SQL, Power BI, and data privacy regulations. Familiarity with Microsoft Purview, Power Query, Power Automate, Primavera P6, 3DEXPERIENCE, Workday, Data Lineage, Master Data Management, or Data Lake architectures represents an advantage.
  • Minimum 3 years of experience in industrial manufacturing, shipbuilding, production planning, supply chain, quality management, business analysis, or data administration, including work with large operational datasets and business systems. Experience with ERP implementations, data quality initiatives, digitalization projects, or Data Steward/Business Analyst roles is highly valued.
  • Ability to analyze large datasets, identify data quality issues and root causes, translate business requirements into data rules and standards, maintain clear documentation, and collaborate effectively across multiple business functions. Experience facilitating workshops, delivering user training, and presenting findings to stakeholders is a plus.
  • Ability to communicate confidently in English, both orally and in writing.
  • Analytical, detail-oriented, and results-driven professional with strong communication, stakeholder management, influencing, negotiation, and problem-solving skills. Demonstrates integrity, accountability, resilience to change, and the ability to work effectively in a dynamic and evolving environment while promoting data quality and continuous improvement.
  • Eligible to obtain access rights to company information systems and comply with company health, safety, security, confidentiality, and data protection requirements.

What We Offer

  • The opportunity to contribute to data governance and digital transformation initiatives within a complex business environment.
  • A cross-functional role with exposure to business processes, IT systems, data quality, and continuous improvement.
  • The opportunity to work with modern data management and analytics technologies.
  • A collaborative environment where your expertise can directly contribute to improving the quality and reliability of business data.

Recruiter:

Teodora Grigore

Email:

[email protected]

Please apply through the Apply Button. Due to GDPR reasons we cannot accept applications by email.

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