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Senior Data Modeller

ItransitionIkona lokalizacjiGlobalnie

Żródlo publikacji: JustJoin.it
Rodzaj zatrudnienia
Rodzaj zatrudnieniaPełny etat
Doświadczenie
DoświadczenieSenior
Dodano
Dodano23 lipca 2026
Wykryte przez nas
Wykryte przez nas24 lipca 2026
Zarobki
ZarobkiDo uzgodnienia

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 such clients as PayPal, Wargaming, Xerox, Philips, Adidas and Toyota.

  • Competitive compensation that depends on your qualification and skills.

  • Career development system with clear skill qualifications.

  • Flexible working hours aligned to your schedule.

  • Options to work remotely.

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