Data Governance Officer

As a Data Governance Officer at Inetum, you will engage in various essential tasks including validating project objectives with the data strategy, structuring information within our Information Systems, and managing data models while ensuring compliance with our data framework policies. You'll also be responsible for enhancing our Data Architecture Framework and defining data management policies that promote effective governance across projects.

To become a Data Governance Officer at Inetum, you should hold a Bachelor's or Master's Degree coupled with at least three years of experience in consulting or data governance projects. Familiarity with data governance tools such as Informatica and knowledge of frameworks like TOGAF or COBIT are also crucial for success in this role.

Yes, Inetum provides a hybrid work model for Data Governance Officers, with the flexibility to work from home for two to three days each week. This allows you to enjoy a work-life balance while still being a vital part of the team in the Lisbon office.

Ideal candidates for the Data Governance Officer role at Inetum should have experience with various data governance tools, including Informatica, Microsoft Purview, and Collibra. Additionally, familiarity with project management tools like Jira and Confluence, as well as knowledge of Enterprise Architecture tools, will be beneficial.

A Data Governance Officer at Inetum should possess strong analytical and organizational skills, excellent communication abilities, and a collaborative spirit. Strong proficiency in English is mandatory, and knowledge of other languages will be advantageous. These skills will enable you to work effectively both independently and as part of a team.

When addressing your experience with data governance tools, be specific about the tools you've used, such as Informatica or Collibra. Provide examples of how you utilized these tools for managing data compliance and governance, highlighting any measurable outcomes or improvements you achieved.

Discuss your methodology for defining data management policies, emphasizing collaboration with stakeholders and alignment with project objectives. Highlight any frameworks you utilize, like COBIT or DAMA, and your focus on best practices to ensure robustness in governance.

Share a specific scenario detailing the challenges you faced, the steps you took to address them, and the positive outcomes that resulted. This not only reflects your problem-solving abilities but also your practical experience in data governance.

Explain your strategies for fostering open lines of communication, such as regular updates through meetings or project management tools like Confluence. Stress the importance of keeping all parties informed to ensure project alignment and success.

Discuss your experience creating and managing data models, explaining the tools you used and your understanding of compliance with data governance policies. Mention specific projects where your data modeling contributed to a more efficient data management process.

Mention any professional development activities you engage in, such as attending webinars, following industry publications, or participating in relevant forums. Highlight how continuous learning helps you bring fresh insights and practices into your role.

Emphasize the critical role that data governance plays in ensuring compliance, protecting sensitive information, and enhancing data quality in the banking sector. Discuss any personal views on regulations and how governance impacts customer trust.

Provide an example of a specific situation where your contributions led to enhancements in a data architecture framework. Focus on methodological improvements and the benefits they delivered to project outcomes or business intelligence.

Talk about your familiarity with Enterprise Architecture frameworks, particularly TOGAF. Detail how you've applied its principles in your past work, possibly with examples, to outline how it aided in structuring the organization's data governance efforts.

Explain your analytical approach to refining data processes, such as root cause analysis and process mapping. Provide specific techniques you utilize to streamline processes and improve decision-making capabilities.