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# Senior Data Engineer - Snowflake & Tableau

- **Company:** Editx Bv
- **Location:** Beerse, Belgium
- **Experience:** Expert
- **Contract:** Temporary contract
- **Skills:** Artificial Intelligence, Architectural Patterns, Cloud Computing, Information Engineering, Extract Transform Load (ETL), Data Transformation, Data Systems, Network Layer, Machine Learning, Performance Tuning, Planisware, Power BI, SAP HANA, SQL Databases, Systems Integration, Tableau (Software), Enterprise Data Management, Snowflake, Build Management, Data Management, Data Inconsistencies, Data Pipelines, Legacy Systems
- **Published:** September 16, 2026
- **Apply:** https://europa.eu/eures/portal/jv-se/jv-details/MGJiNDQwYmYtOTQyMS00MzE0LWE2MDItOTQ3ZmEyZDFiYzM4IDM?lang=en

## About the Role

* 8+ years of data engineering experience focusing on Snowflake and expert-level SQL.
 * 8+ years of experience in business intelligence using Tableau (Desktop and Prep) and Power BI.
 * Extensive experience designing ETL/ELT frameworks and data transformation pipelines.
 * In-depth functional knowledge of portfolio planning, resource forecasting, and financial planning.
 * Proven expertise in data modeling and performance optimization for large-scale transformations.
 * Strong experience integrating cross-domain enterprise data from systems like SAP HANA.
 * You possess strong problem-solving and root cause analysis skills to resolve cross-system data inconsistencies.
 * You bring exceptional technical communication skills to engage with both IT and business stakeholders.
 * You are fluent in English.

Nice to Haves

 * Experience with Planisware for portfolio and project data management.
 * Knowledge of practical AI/ML applications and building flows with Copilot.
 * Active knowledge of Dutch.

## Description

* Design and build Layer 3 data models and scalable ETL/ELT pipelines in a cloud environment.
 * Integrate disparate data sources including demand, supply, and financial actuals into unified datasets.
 * Develop and maintain advanced transformation flows to support migrations from legacy systems to modern architectures.
 * Translate ambiguous business requirements into structured data solutions and actionable insights.
 * Enable scalable reporting by building robust data models and dashboards for executive decision-making.
 * Identify pragmatic AI use cases for forecasting improvements and trend detection.


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