Data Modeler - Remote Job.

As a Data Modeler at our company, your key responsibilities will include designing, implementing, supporting, and maintaining relational database model systems. You will work closely with technical teams to create both logical and physical data models, specifically focusing on clinical data structures. This role also involves reverse engineering existing systems and managing repository activities, ensuring data integrity and functionality.

To qualify for the Data Modeler position, you should have a minimum of 5 years of experience in data modeling, particularly within clinical environments. Familiarity with tools like Erwin is essential, as well as expertise in designing and managing logical and physical data models. An understanding of reverse engineering and repository management is also required, alongside advanced English proficiency.

Yes, the Data Modeler position is fully remote! However, it is exclusively available for candidates residing in Latin America. We believe in offering flexibility while ensuring that our team remains connected and collaborative across borders.

The Data Modeler role operates under an independent contractor model. This means that the contract does not include tax withholding or insurance and will only cover your gross payment for hours worked, allowing for more flexibility in your work arrangement.

For the Data Modeler role, we expect you to work full-time, which is 40 hours per week from 9 AM to 5 PM EST USA. This schedule allows for clear communication and collaboration with clients and team members across different time zones.

Certainly! When answering this question, emphasize your hands-on experience with Erwin or similar data modeling tools. Discuss specific projects where you utilized these tools effectively to design and manage complex data models, and the outcomes of those projects.

Highlight your process for maintaining data integrity, such as performing regular audits, employing validation techniques, and utilizing repository management strategies. Be specific about your methodologies and share any successful strategies you've implemented in previous roles.

Discuss your collaborative mindset and how you communicate effectively with cross-functional teams. Mention the importance of regular meetings, updating stakeholders, and seeking input from developers and analysts to create a successful work environment.

Here, share a specific project that presented challenges, detail the obstacles, and outline how you managed them. Discuss tools, strategies, and on-the-fly problem-solving approaches that led to a successful outcome, showcasing your analytical skills.

Explain your step-by-step approach to reverse engineering, including assessing the existing documentation, using data profiling tools, and collaborating with legacy system experts. Emphasize the importance of understanding the context and ensuring the new model is robust.

Demonstrate your commitment to continuous learning by mentioning relevant resources, such as professional associations, online courses, webinars, and industry publications. Discuss how you apply these new insights into your day-to-day duties as a Data Modeler.

Discuss the blend of technical skills, analytical ability, communication, and problem-solving prowess that contributes to a successful Data Modeler. Share examples of how these traits have positively influenced your work in the past.

Share a specific example where you've faced challenges with a data model and the steps you took to optimize it. Explain how this optimization improved performance or usability and what metrics you used to measure success.

Discuss your techniques for breaking down complex datasets into manageable components, using documentation practices, and leveraging tools for visualization and analysis. Mention the importance of organization and prioritization in managing data effectively.

Describe your conflict resolution strategies, such as open communication, active listening, and seeking common ground. Share a specific instance where you helped resolve a disagreement in a way that strengthened team dynamics.