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Data Modeler
Data Warehouse Modeler and Engineer (DBT, Snowflake) – EMEA, Data Solutions (Critical Role)
This critical role is expanding the Data Solutions team in EMEA, seeking a talented and experienced Data Warehouse Modeler and Engineer focused on Snowflake and dbt.
About the Role
As a key contributor, you will design and implement end-to-end data integration and transformation solutions using ETL/ELT principles, combining data modeling, mapping, transformation, and hands-on engineering with dbt.
Key Responsibilities
- Design and implement ETL/ELT pipelines for:
- Data ingestion
- Transformation
- Consolidation into Snowflake
- Perform data mapping from source systems to target Snowflake structures
- Develop, maintain, and optimise:
- Conceptual, logical, and physical data models
- Staging & integration mart schemas
- Develop, test, and maintain dbt models, following best practices
- Optimise Snowflake performance, including:
- Query design
- Materialisations
- Clustering strategies
- Ensure:
- Data quality, consistency, and lineage
- Thorough documentation of configurations
- Collaborate with engineering, analytics, and platform teams to:
- Define data patterns and standards
- Align on technical requirements
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Technical Qualifications
Education & Experience Required
- Bachelor’s or Master’s degree in:
- Computer Science
- Data Engineering, or a related technical field
- Extensive industry experience in a fast-paced, enterprise-scale environment
Technical Skills (Core Competencies)
Snowflake & Data Engineering
- Strong proven proficiency in SQL
- Hands-on experience with:
- dbt Core or dbt Cloud (one required, other a plus)
- Traditional ETL tools:
- ODI
- Informatica
- Talend
- SSIS
- Deep expertise in:
- Snowflake data engineering architecture
- SQL data modeling (Kimball, Inmon, Data Vault concepts)
- ETL/ELT design and data mapping
- Data quality & governance
- Performance optimisation strategies
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Scaling & Cloud Awareness (Nice to Have)
- Familiarity with the AWS data stack, including:
- S3
- AWS Glue
- EMR
- PySpark
- Iceberg
Non-Technical Skills
- Strong ownership and accountability ethos
- Analytical rigor, with open curiosity to:
- Improve methods
- Troubleshoot challenges
- Identify inefficiencies autonomously
- Technical storytelling skills:
- Excellent written & verbal communication
- Requires an AI-relevant mindset (preferably with related experience)
Mandatory Focus: Snowflake specialisation with dbt experience.
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