VP Data modeler – Data Office

Job Description

• Analyze and translate business needs to create solution data models.
• Evaluate current data systems.
• Work with data analysts, data architects, engineers, and database administrators to design conceptual data models and data flows.
• Develop standard data coding practices to ensure system-wide consistency.
• Evaluate changes to existing systems for cross-compatibility.
• Implement data strategies and create physical data models.
• Update and improve local and metadata models.
• Assess implemented data systems to identify variances, discrepancies, and efficiency gaps.
• Troubleshoot and optimize data systems.
• Communicate with internal or external stakeholders to provide guidance, direction, and MIS-related information.

Must Have

• Strong management skills.
• Strong analytical and problem-solving skills to effectively design data solutions.
• High attention to detail and commitment to delivering high-quality work.
• Excellent communication and teamwork skills to collaborate with cross-functional teams.
• Ability to manage time effectively and prioritize tasks in a dynamic work environment.
• Digital logic skills to clean and organize unstructured data.
• Solid understanding of computer architecture and organization to maximize data processing efficiency.
• Knowledge of data representation techniques for effective data gathering, manipulation, and analysis.
• Understanding of memory architecture to balance speed, durability, reliability, and cost-effectiveness without compromising data integrity.
• Familiarity with the Erwin data modeling tool.
• Ability to adapt to new data modeling methodologies.
• Proficiency in SQL and its implementation.
• Hands-on experience with database systems, including RDBMS capable of handling large-scale data efficiently.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.
• Demonstrated expertise in working with Databricks for data processing and analysis.
• Experience implementing and optimizing data solutions using multiple programming languages in an Azure environment.
• Cloud technology certifications are an added advantage.

Experience

• Proven experience managing a technical team.
• 7–10 years of hands-on experience in data engineering, including developing data pipelines and managing data infrastructure in Azure.
• Strong Python and SQL experience, with exposure to end-to-end data product deployment.