Technical Data Modeller (ID 3613)

Amsterdam - Netherlands

Monthly Salary: Not Disclosed

Experience Required: 10years

Posted on: Yesterday

Vacancies: 1 Vacancy

Job Summary

As a Technical Data Modeller you will:

Design develop and maintain conceptual logical and physical data models across enterprise data platforms.
Translate business and regulatory requirements into scalable and robust technical data structures.
Design and validate dimensional models including factdimension models star schema and snowflake schema.
Ensure data quality lineage governance and consistency within Finance and Risk data domains.
Work closely with Data Engineers Product Owners Data Office and Architecture teams to implement and optimize data models.
Implement and support data modelling solutions on Azure SQL Database Azure Databricks and Azure Data Factory.
Review and optimize existing data models while providing guidance on data standards and modelling best practices.
Support data ingestion and transformation teams during the implementation and delivery phases.
Participate in technical discussions architecture reviews and refinement sessions to ensure scalable data solutions.
Contribute to building compliant scalable and high-quality data structures that support analytics and regulatory reporting.

What You Bring to the Table:

10 years of experience in Data Modelling Data Architecture or related data engineering roles within complex environments.
Strong expertise in SQL including complex queries performance tuning and relational database design.
Hands-on experience designing conceptual logical and physical data models.
Proven experience working with the Azure data ecosystem including Azure SQL Database Azure Databricks and Azure Data Factory.
Strong understanding of financial data domains including payments credit risk regulatory and reporting datasets.
Deep knowledge of data modelling techniques including normalization and denormalization star and snowflake schemas factdimension modelling Slowly Changing Dimensions (SCD) and metadata and lineage management.
Strong communication skills and the ability to collaborate effectively with both technical and business stakeholders.
Experience with regulatory reporting environments such as DNB AFM IFRS and Risk & Finance reporting is considered an advantage.
Familiarity with DevOps practices including Azure DevOps pipelines and Git.
Exposure to data governance frameworks and data quality practices.
Experience working within banking or financial services environments is preferred.

You Should Possess the Ability to:

Translate complex business and regulatory requirements into scalable technical data models.
Design and optimize enterprise-level data structures that support analytics and reporting platforms.
Collaborate effectively with cross-functional teams including engineers architects product owners and business stakeholders.
Ensure high standards of data quality governance compliance and consistency across data platforms.
Evaluate and improve existing data models while recommending technical enhancements and best practices.
Work independently challenge requirements when necessary and propose robust technical solutions.
Contribute to architecture discussions and support the continuous improvement of data platform capabilities.

What We Bring to the Table:

Opportunity to work on large-scale enterprise data platforms within a complex and evolving data environment.
Exposure to modern cloud-based technologies within the Azure data ecosystem.
A collaborative working environment alongside experienced data engineers architects and domain experts.
The opportunity to contribute to high-impact data initiatives supporting financial analytics and regulatory reporting.
A technically challenging environment that encourages innovation ownership and continuous improvement in data modelling practices.

Required Skills:

As a Technical Data Modeller you will: Design develop and maintain conceptual logical and physical data models across enterprise data platforms. Translate business and regulatory requirements into scalable and robust technical data structures. Design and validate dimensional models including factdimension models star schema and snowflake schema. Ensure data quality lineage governance and consistency within Finance and Risk data domains. Work closely with Data Engineers Product Owners Data Office and Architecture teams to implement and optimize data models. Implement and support data modelling solutions on Azure SQL Database Azure Databricks and Azure Data Factory. Review and optimize existing data models while providing guidance on data standards and modelling best practices. Support data ingestion and transformation teams during the implementation and delivery phases. Participate in technical discussions architecture reviews and refinement sessions to ensure scalable data solutions. Contribute to building compliant scalable and high-quality data structures that support analytics and regulatory reporting. What You Bring to the Table: 10 years of experience in Data Modelling Data Architecture or related data engineering roles within complex environments. Strong expertise in SQL including complex queries performance tuning and relational database design. Hands-on experience designing conceptual logical and physical data models. Proven experience working with the Azure data ecosystem including Azure SQL Database Azure Databricks and Azure Data Factory. Strong understanding of financial data domains including payments credit risk regulatory and reporting datasets. Deep knowledge of data modelling techniques including normalization and denormalization star and snowflake schemas factdimension modelling Slowly Changing Dimensions (SCD) and metadata and lineage management. Strong communication skills and the ability to collaborate effectively with both technical and business stakeholders. Experience with regulatory reporting environments such as DNB AFM IFRS and Risk & Finance reporting is considered an advantage. Familiarity with DevOps practices including Azure DevOps pipelines and Git. Exposure to data governance frameworks and data quality practices. Experience working within banking or financial services environments is preferred. You Should Possess the Ability to: Translate complex business and regulatory requirements into scalable technical data models. Design and optimize enterprise-level data structures that support analytics and reporting platforms. Collaborate effectively with cross-functional teams including engineers architects product owners and business stakeholders. Ensure high standards of data quality governance compliance and consistency across data platforms. Evaluate and improve existing data models while recommending technical enhancements and best practices. Work independently challenge requirements when necessary and propose robust technical solutions. Contribute to architecture discussions and support the continuous improvement of data platform capabilities. What We Bring to the Table: Opportunity to work on large-scale enterprise data platforms within a complex and evolving data environment. Exposure to modern cloud-based technologies within the Azure data ecosystem. A collaborative working environment alongside experienced data engineers architects and domain experts. The opportunity to contribute to high-impact data initiatives supporting financial analytics and regulatory reporting. A technically challenging environment that encourages innovation ownership and continuous improvement in data modelling practices.

As a Technical Data Modeller you will:

Design develop and maintain conceptual logical and physical data models across enterprise data platforms.
Translate business and regulatory requirements into scalable and robust technical data structures.
Design and validate dimensional models including factdimension models star schema and snowflake schema.
Ensure data quality lineage governance and consistency within Finance and Risk data domains.
Work closely with Data Engineers Product Owners Data Office and Architecture teams to implement and optimize data models.
Implement and support data modelling solutions on Azure SQL Database Azure Databricks and Azure Data Factory.
Review and optimize existing data models while providing guidance on data standards and modelling best practices.
Support data ingestion and transformation teams during the implementation and delivery phases.
Participate in technical discussions architecture reviews and refinement sessions to ensure scalable data solutions.
Contribute to building compliant scalable and high-quality data structures that support analytics and regulatory reporting.

What You Bring to the Table:

10 years of experience in Data Modelling Data Architecture or related data engineering roles within complex environments.
Strong expertise in SQL including complex queries performance tuning and relational database design.
Hands-on experience designing conceptual logical and physical data models.
Proven experience working with the Azure data ecosystem including Azure SQL Database Azure Databricks and Azure Data Factory.
Strong understanding of financial data domains including payments credit risk regulatory and reporting datasets.
Deep knowledge of data modelling techniques including normalization and denormalization star and snowflake schemas factdimension modelling Slowly Changing Dimensions (SCD) and metadata and lineage management.
Strong communication skills and the ability to collaborate effectively with both technical and business stakeholders.
Experience with regulatory reporting environments such as DNB AFM IFRS and Risk & Finance reporting is considered an advantage.
Familiarity with DevOps practices including Azure DevOps pipelines and Git.
Exposure to data governance frameworks and data quality practices.
Experience working within banking or financial services environments is preferred.

You Should Possess the Ability to:

Translate complex business and regulatory requirements into scalable technical data models.
Design and optimize enterprise-level data structures that support analytics and reporting platforms.
Collaborate effectively with cross-functional teams including engineers architects product owners and business stakeholders.
Ensure high standards of data quality governance compliance and consistency across data platforms.
Evaluate and improve existing data models while recommending technical enhancements and best practices.
Work independently challenge requirements when necessary and propose robust technical solutions.
Contribute to architecture discussions and support the continuous improvement of data platform capabilities.

What We Bring to the Table:

Opportunity to work on large-scale enterprise data platforms within a complex and evolving data environment.
Exposure to modern cloud-based technologies within the Azure data ecosystem.
A collaborative working environment alongside experienced data engineers architects and domain experts.
The opportunity to contribute to high-impact data initiatives supporting financial analytics and regulatory reporting.
A technically challenging environment that encourages innovation ownership and continuous improvement in data modelling practices.