Senior Data Modeller

We are seeking a talented Senior Data Modeler - Analytical Solutions to lead the design of enterprise-scale analytical Data Vault 2.0 models for a data platform built on Databricks. We are looking for a candidate whose expertise is rooted in foundational data modelling principles rather than a single vendor.

In this role, you will define shared analytical models and standards that ensure consistency, reusability, and trust across the enterprise. This position offers a unique opportunity to lead the architectural transformation of a complex legacy environment into a streamlined, future-ready data asset, while building a versatile profile to drive data strategy across any modern cloud environment.

Requirements

• 5+ years of dedicated experience in data modelling (not deep hands-on engineering).
• Hands-on experience with modern cloud data platforms (Databricks).
• Strong experience with SQL. Familiarity with Python/PySpark is a plus.
• Deep knowledge of modeling approaches such as Kimball, Inmon, and Data Vault 2.0, with the ability to select the most appropriate methodology to address specific business challenges.
• Experience with enterprise-grade modelling tools (e.g., ER/Studio, Erwin, or Sparx EA).
• Strong soft skills and non-confrontational behavior.

Nice to have

• Model enterprise-level analytical Data Vault 2.0 structures on Databricks, handling both structured and semi-structured data.
• Create and maintain data mapping artifacts to support analytics, integration, and migration initiatives.
• Establish modeling patterns suitable for lakehouse, medallion, and semantic-layer architectures.
• Ensure alignment between physical analytical models and enterprise semantic definitions.
• Act as the primary interface between business stakeholders and data engineering, focusing strictly on data modeling rather than hands-on engineering.
• Translate complex business logic into high-quality documentation, data lineage, and precise models for engineering implementation.
• Conduct deep-dive sessions to audit and remediate complex or poorly structured data assets in the current environment.
• Establish enterprise data modeling standards that prioritize data integrity, portability, and long-term flexibility.
• Lead data profiling activities to ensure physical implementations align with defined data models.

We offer

• Projects for clients such as PayPal, Wargaming, Xerox, Philips, Adidas, and Toyota.
• Competitive compensation that depends on your qualifications and skills.
• Career development system with clear skill qualifications.
• Flexible working hours aligned to your schedule.
• Options to work remotely.