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# Data Engineer

- **Company:** Xyntrel Tech Talents
- **Location:** Amsterdam, Netherlands
- **Experience:** Expert
- **Salary:** €542.0 - €833.0
- **Contract:** Permanent contract
- **Skills:** Airflow, Amazon Web Services, Microsoft Azure, BigQuery, Information Engineering, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Warehousing, Data Intelligence, Python (Programming Language), SQL Databases, Workflow Management Systems, Cloud Platform System, Snowflake, Data Lakes, Software Coding, Data Pipelines, Databricks
- **Published:** May 17, 2026
- **Apply:** https://www.careerjet.nl/jobad/nl205efd60714a084231f255e6c0de6f47

## About the Role

* 5+ years of experience in a data engineering or similar role.
 * Proven expertise in building and managing ETL/ELT processes, data lakes, and data warehouses.
 * Strong proficiency in Python, SQL, DBT, and modern data platforms (e.g., Snowflake, BigQuery, Databricks, or similar).
 * Experience with cloud environments (preferably AWS, Azure, or GCP).
 * Familiarity with orchestration tools like Airflow, Prefect, or Dagster.
 * Ability to balance hands-on coding with strategic architecture planning.
 * Strong interpersonal skills - you value connection, mentorship, and collaboration.
 * Fluent in English and Dutch.

## Description

As a Data Engineer, you'll lead the design and development of advanced data solutions that empower organizations to make intelligent data-driven decisions. You'll work alongside a collaborative team where your personality, ideas, and ambitions matter just as much as your technical skills.
If you're passionate about transforming complex data into meaningful insights - and doing it in a workplace where you're genuinely valued - we'd love to meet you.
De vacature
Your Responsibilities

 * Design, build, and maintain scalable and reliable data pipelines and architectures.
 * Lead complex data integration projects across multiple systems and data sources.
 * Collaborate closely with data scientists, analysts, and business stakeholders to translate business needs into technical solutions.
 * Optimize data workflows for efficiency, reliability, and maintainability.
 * Evaluate and implement new tools, technologies, and methodologies to enhance our data infrastructure


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