Data Modeller for Audit-Ready Enterprise DW (Hybrid)

emagine Group; Stockholms kommun; Hybrid; SEK 700,000 - 900,000; Full time

Job summary

emagine Group is seeking a Data Modeller to build an audit-ready data warehouse for Finance & Risk in a banking client context. The role emphasizes Data Vault 2.0 modelling, scalable data platforms, and strong collaboration with data engineers and business stakeholders.

You will design robust data models, implement ELT pipelines on Google Cloud Platform (BigQuery, Cloud Composer, dbt, Dataform), and ensure data quality, lineage, and regulatory compliance across the enterprise.

Qualifications

• Deep expertise in data modelling and enterprise data warehouse design.
• Hands-on experience delivering data models from requirements to production implementation.
• Experience with scalable data platforms integrating many source systems.
• Ability to balance business needs, regulatory requirements, and maintainability.
• Strong communication and collaboration to translate requirements into practical data solutions.

Responsibilities

• Take accountability for implementing and maintaining physical data models in the target data platform.
• Design target data models using Data Vault 2.0 principles and scalable patterns.
• Build and optimize ELT processes using GCP technologies such as BigQuery, Cloud Composer, dbt and Dataform.
• Promote standards for historical data management, lineage, metadata, and data quality.
• Drive best practices in data modelling and warehouse design across the team.

Skills

SQL

Python

Data modelling

Data warehouse design

Data governance

ETL/ELT

BigQuery

dbt

Data vault 2.0

Tools

dbt

Dataform

Cloud Composer

Apache Airflow

GCP

Job description

emagine Group is seeking a Data Modeller to build an audit-ready data warehouse for Finance & Risk in a banking client context. The role emphasizes Data Vault 2.0 modelling, scalable data platforms, and strong collaboration with data engineers and business stakeholders.

You will design robust data models, implement ELT pipelines on Google Cloud Platform (BigQuery, Cloud Composer, dbt, Dataform), and ensure data quality, lineage, and regulatory compliance across the enterprise.