Data engineer

Infinity Quest; Amsterdam; On-site; EUR 90,000 - 130,000; Full time

Job summary

Infinity Quest in Amsterdam seeks a Senior Data Analytics Engineer to design and build scalable data pipelines and analytics solutions. You will translate complex datasets into business-ready data, partner with business and tech stakeholders, and ensure data quality through validation and monitoring.

The role emphasizes advanced SQL and Python, data warehousing, and modern tooling like dbt and Snowflake within a CI/CD culture. This is a senior, hands-on data engineering position.

Qualifications

• Experience designing and maintaining scalable data pipelines and ETL processes.

Responsibilities

• Design, develop and maintain scalable data pipelines and ETL processes.
• Build and optimize data warehouses, data models and SQL transformations.
• Analyze complex datasets and translate business requirements into actionable insights.
• Work with business and technical stakeholders to deliver data solutions.
• Implement data quality checks, validation and monitoring.
• Contribute to data architecture, system design and analytics solutions.
• Follow engineering best practices, including version control and CI/CD.

Skills

SQL

Python

Data pipelines

Data engineering

Analytics engineering

ETL

dbt

Tools

dbt

Snowflake

AWS

CI/CD

Data warehousing

Job description

We are looking for a Senior Data Analytics Engineer with strong experience in both Data Engineering and Analytics Engineering. The role involves building scalable data pipelines, transforming complex datasets into reliable business-ready data, and delivering actionable insights to support data-driven decision-making.

• Design, develop and maintain scalable data pipelines and ETL processes.
• Build and optimize data warehouses, data models and SQL transformations.
• Analyze complex datasets and translate business requirements into actionable insights.
• Work with business and technical stakeholders to deliver data solutions.
• Implement data quality checks, validation and monitoring.
• Contribute to data architecture, system design and analytics solutions.
• Follow engineering best practices, including version control and CI/CD.
• Advanced SQL and Python.
• dbt (Data Build Tool).
• Snowflake and AWS.
• Data Warehousing and Data Modelling.
• Data Quality and Validation.
• Data Architecture and System Design.