Snowflake/dbt Consultant

Next Ventures; Brussel; Hybride; EUR 70 000 - 110 000; Plein temps

Résumé du poste

Next Ventures in Belgium seeks a Data Engineering Consultant specializing in Snowflake and dbt to help consolidate fragmented data into a trusted platform. You will design ingestion pipelines, build modular dbt models, and develop dimensional datasets for executive reporting and analytics.

The role emphasizes automated testing, data lineage, and CI/CD practices, with hybrid/remote options to suit project needs across the client environment.

Qualifications

• Extensive experience with Snowflake and dbt in enterprise data platforms.
• Strong SQL and data modeling skills.
• Familiarity with data warehousing concepts and best practices.

Responsabilités

• Design scalable ingestion pipelines into Snowflake from business apps, APIs and databases.
• Develop modular dbt models across staging, intermediate and reporting layers.
• Create dimensional models and curated datasets for Power BI/Tableau reporting.
• Implement automated tests, data freshness checks, and lineage documentation.

Connaissances

Snowflake

dbt

SQL

Data Modeling

CI/CD

Outils

Power BI

Tableau

Git

Description du poste

*HELP TURN A DATA PLATFORM INTO A BUSINESS ADVANTAGE - SNOWFLAKE & DBT CONSULTANT NEEDED - 6-12 MONTH INITIAL ENGAGEMENT - HYBRID/REMOTE ON OFFER*

I am supporting one of my key customers in Belgium who are looking to add a Data Engineering Consultant with strong expertise across Snowflake and dbt for an enterprise data platform project. The programme focuses on bringing fragmented operational and commercial data into Snowflake, building trusted data models, and enabling self-service analytics and downstream AI use cases.

The key areas of involvement would include:

• Designing scalable ingestion pipelines into Snowflake from business applications, APIs and databases, supporting batch and incremental processing.
• Developing modular dbt models across staging, intermediate and reporting layers, using SQL, incremental materialisations, snapshots and reusable macros.
• Building well-structured dimensional models and curated datasets for Power BI/Tableau reporting, customer analytics and operational insights.
• Embedding automated testing, source freshness checks, documentation and lineage to improve data quality and confidence in business reporting.
• Optimising Snowflake performance and cost through query tuning, warehouse sizing, workload management and appropriate clustering strategies.
• Strengthening Git-based development and CI/CD, including pull-request reviews, environment management and controlled deployments.

Beyond delivery, there would be scope to work closely with analysts, architects and business stakeholders, translating requirements into reliable data products and helping establish sustainable engineering practices.