Data Documentalist / Data Governance - (Remote - Portugal or Spain)

As a Data Documentalist at Jobgether, your main responsibilities include creating and maintaining Data Dictionaries, Business Glossaries, and Data Lineage frameworks. You will analyze technical documentation related to data structures, APIs, and database models to ensure they align with governance standards. Collaborating with business stakeholders and system providers will be crucial to define and ensure the accuracy of data structures, making sure data governance practices are adhered to and improved continuously.

To succeed as a Data Documentalist at Jobgether, you should have proven experience in data governance, management, or a related field. The ability to interpret and work with technical documentation, such as APIs and database models, is essential. Strong communication skills for stakeholder engagement, proficiency in SQL and Python, and experience with data governance models like Data Dictionaries and Business Glossaries will make you a strong candidate.

Yes, the Data Documentalist position at Jobgether is a remote opportunity! You can work from anywhere in Portugal or Spain, allowing for flexibility in your work schedule while contributing to exciting data governance projects.

In your role as a Data Documentalist at Jobgether, you’ll utilize various tools and technologies including SQL and Python for data analysis and management. Familiarity with Data Catalog tools such as Atlan will also be beneficial in your day-to-day tasks focused on maintaining data governance standards.

Jobgether is committed to your growth! As a Data Documentalist, you will have access to professional development resources, including training and certifications. This ensures that you can stay up-to-date with the latest industry practices in data governance and management.

A solid answer would discuss the principles of data governance, highlighting its importance in maintaining data quality, compliance, and security. You could mention that effective data governance ensures that data is accurate, consistent, and used responsibly across all organizational departments.

When discussing this, emphasize the systematic approach you take: conducting regular reviews, utilizing feedback from stakeholders, and implementing automated tools if available. Stress the importance of collaboration across departments to maintain data accuracy.

Select a specific instance where you encountered a challenge, such as discrepancies in data quality. Discuss the diagnostic steps you took, the stakeholders involved, and how your collaborative and analytical skills helped solve the issue effectively.

Explain your hands-on experience, perhaps highlighting specific projects where you interpreted technical documentation, analyzed data structures, and ensured they align with governance standards. Be prepared to provide examples around your problem-solving abilities in this context.

Discuss methods like stakeholder interviews, workshops, or regular updates that ensure open lines of communication. Highlight the importance of understanding their needs and incorporating their insights into data governance practices.

Mention resources you use such as industry certifications, webinars, or relevant forums. Highlight the importance of continuous learning in keeping data governance practices relevant to regulatory requirements and business needs.

Offer a concrete example illustrating steps you took to analyze data, engage with stakeholders, and implement improvements. Discuss the positive outcomes your initiatives had on data integrity and access throughout the organization.

Discuss the pivotal role of data lineage in tracing data origins, transformations, and uses. Highlight it as a foundational element for compliance, transparency, and error traceability, essential to maintaining data integrity.

If applicable, share your experiences with specific Data Catalog tools. Discuss how they aided in managing metadata and supported data governance initiatives, emphasizing your proficiency and effectiveness in handling them.

Explain your collaborative approach in aligning data standards across departments. Highlight the importance of regular communication, establishing common guidelines, and actively ensuring adherence through ongoing dialogue and feedback.