Data Modeller

Job Description

What You Will Do

• As a data modeler, your responsibilities will include:
• Analyzing and translating business needs to create solution data models
• Evaluating current data systems
• Working with data analysts, data architects, engineers and database administrators to design conceptual data models and data flows
• Developing ideal data coding practices to ensure consistency within the system.
• Evaluating changes to existing systems for cross-compatibility.
• Implementing data strategies and creating physical data models
• Updating and improving local and metadata models
• Assessing implemented data systems to look for variances, discrepancies, and efficiency
• Troubleshooting and optimizing data systems
• Technical skills:
• Digital logic: it is important to possess this skill to clean and organize an unstructured set of data.
• Computer architecture and organization: A solid understanding of computer architecture and organization will enable you to maximize efficiency when working with data.
• Data representation: This allows for easier gathering, manipulation, and analysis of data, which can save valuable time and money.
• Memory architecture: The most important part of memory architecture is being able to find the method that best combines speed, durability, reliability, and cost-effectiveness while not compromising the integrity of the data.
• Familiarity with Erwin modeling tool.
• Adapt to new modeling methods.
• SQL language and its implementation.
• Sufficient experience using database systems: Relational Database Management Systems (RDBMS) that possess big data handling capabilities, such as the ability to quickly store and fetch data.

What We Are Looking For

• 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 in implementing and optimizing data solutions using multiple programming languages in an Azure environment.
• People Management experience is essential.
• 7-10 years experience in Data Engineering of hands-on experience in developing data pipelines and managing data infrastructure within Azure.
• Python and SQL experience required
• Experience in end-to-end Data Product deployment

What We Are Not Looking For

❌ Opaque Problem Solvers

• Approaches that prioritize complexity over clarity, with limited focus on explainability, governance, or confidence in decision‑making outcomes.
• ❌ Isolated Specialists
• Individuals who operate in silos and lack the inclination to co‑create with product, engineering, and business partners to drive end‑to‑end impact.
• ❌ Comfort‑Zone Practitioners
• Skillsets rooted in legacy methodologies, with minimal appetite for evolving alongside modern cloud architectures, MLOps maturity, and GenAI‑driven innovation.
• What’s In It For You.
• Pay for performance culture (Competitive and performance-linked compensation)
• Diverse workforce and inclusive culture
• Career development and growth opportunities by design
• Work with the best minds in the field
• Get opportunities to bring your whole self to the organization and perform to your best.