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# Data Analytics Engineer / Architect

- **Company:** Eucon GmbH
- **Location:** Amersfoort, Netherlands
- **Contract:** Permanent contract
- **Skills:** Query Performance, Code Review, Data Infrastructure, Data Transformation, Data Vault Modeling, Database Testing, Dimensional Modeling, Machine Learning, Meta-Data Management, Power BI, Feature Engineering, Sql Optimization, Snowflake, Git, Data Lineage, Data Analytics, Sql Tuning, Databricks
- **Published:** July 3, 2026
- **Apply:** https://nl.indeed.com/viewjob?jk=b722c9aa4e165a5b

## About the Role

* Hands-on expertise in Snowflake and its data modeling capabilities for defining business entities, KPIs, and building semantic layers for BI and advanced analytics use cases. Additional experience in Databricks being a plus
 * You bring advanced SQL expertise with a strong focus on transformations and query performance, combined with hands-on experience in dbt (models, tests, macros, and project structure), and a deep understanding of data modeling concepts such as dimensional modeling as well as Data Vault 2.0 and Anchor Modeling (or a strong willingness to learn both)
 * You collaborate effectively with business stakeholders and translate requirements into scalable data models, while maintaining high standards for data quality, harmonization, and single-source-of-truth principles within Git-based development workflows
 * You would stand out with additional knowledge in Power BI (from a consumption perspective), experience with data testing frameworks (e.g., Great Expectations, DQX, Soda), familiarity with data cataloging and lineage tracking, as well as an understanding of feature engineering concepts for future ML use cases

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## Description

* Design, build, and optimize scalable data transformation pipelines with a strong focus on SQL performance and efficiency, while maintaining robust dbt projects including models, tests, macros, and structured project setups
 * Develop and evolve data models using dimensional modeling principles (e.g., star schemas) as well as Data Vault 2.0 and Anchor Modeling approaches in a combined modeling environment
 * Define, standardize, and maintain business entities, KPIs, and metric logic as reusable assets, and provide semantic layers consumable by BI tools and machine learning use cases
 * Work closely with business stakeholders to translate requirements into scalable data models, ensuring alignment, data consistency, and a single-source-of-truth approach
 * Leverage modern data platforms such as Snowflake and/or Databricks and contribute to collaborative, Git-based development workflows including code reviews and best practices


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