The Client

An international pharmaceutical company (Human Pharma) implementing a project to build a modern data warehouse supporting business analytics and regulatory reporting across Europe. The project was conducted in an international setup, with the key operational client located in Barcelona.

The problem

The organization launched a new data warehouse project but lacked a senior professional who could combine analytical and data modeling expertise with the ability to run workshops with business stakeholders.

The key challenges

• the need to design a conceptual and logical data model for the Human Pharma domain,
• linking the logical model with a physical implementation based on dbt,
• the need for clear documentation of the approach and knowledge transfer to the team,
• a new project area without an existing mature data team.

The project required someone more analytical than purely engineering-focused — someone capable of working with business stakeholders, leading workshops, and explaining architectural decisions in business terms.

The solution

Within a staff augmentation model, we provided a Senior Data Modeler available on short notice, with experience in data warehouse projects and regulated environments.

The expert’s profile included:

• practical experience in data modeling (Data Warehousing, Dimensional Modeling, Data Vault 2.0),
• work with Oracle and Snowflake technologies,
• experience in projects based on dbt,
• the ability to connect logical data models with physical implementation,
• strong communication skills in Polish and English (C1 level).

Scope of responsibilities included:

• designing the conceptual and logical data model,
• defining principles for translating logical models into physical implementation in dbt,
• documenting architecture and working standards,
• conducting workshops with the client (including occasional travel to Barcelona),
• supporting the team in building a consistent approach to Data Products.

The conclusions

• A designed and approved conceptual and logical data model for the Human Pharma domain.
• Clear guidelines linking business modeling with technical implementation in dbt.
• Structured documentation and working standards for the newly formed data team.
• Smooth collaboration with the client thanks to the expert’s strong communication skills.

The client quickly secured critical data modeling expertise, minimizing the risk of design errors at the early stage of building the data warehouse.