Data Engineer — Architect of Scalable Data Pipelines

Xyntrel; Amsterdam; Hybrid; EUR 90,000 - 130,000; Full time

Job summary

Xyntrel in Amsterdam is seeking a Data Engineer to design and develop advanced data solutions that empower organizations to make data-driven decisions. You will collaborate with a dedicated team where your personality, ideas and ambitions matter as much as your technical skills.

The role focuses on building scalable data pipelines and architectures, enabling complex data integration across systems, and continuously improving data infrastructure.

Qualifications

• 5+ years of experience as a data engineer or similar role.
• Proven expertise in building and managing ETL/ELT processes, data lakes and data warehouses.
• Strong skills in Python, SQL, DBT and modern data platforms.
• Experience with cloud environments (AWS, Azure or GCP).
• Familiarity with orchestration tools such as Airflow, Prefect or Dagster.
• Ability to code hands-on while thinking strategically about architecture.
• Strong interpersonal skills and collaboration with peers.

Responsibilities

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

Skills

Python

SQL

DBT

Data pipelines

Tools

Snowflake

BigQuery

Databricks

Airflow

Job description

Xyntrel in Amsterdam is seeking a Data Engineer to design and develop advanced data solutions that empower organizations to make data-driven decisions. You will collaborate with a dedicated team where your personality, ideas and ambitions matter as much as your technical skills.

The role focuses on building scalable data pipelines and architectures, enabling complex data integration across systems, and continuously improving data infrastructure.