Data Platform Engineer — Build Scalable Pipelines & Models

Devleaps; Hoofddorp; Hybrid; EUR 60,000 - 85,000; Full time

Job summary

Devleaps is a boutique data, AI, and technology transformation consultancy based in the Netherlands. We design and implement modern data platforms, analytics foundations, and data governance to unlock data value for clients.

As a Data Engineer at Devleaps you will design scalable data pipelines, develop data models, and collaborate with platform engineers and infrastructure specialists to deliver end-to-end data solutions for diverse clients.

Qualifications

• Role requires 4–6 years of data engineering experience.
• Proficiency with data lakehouse architecture.
• Hands-on experience with dbt, SQL and Python.
• Experience with cloud platforms (GCP, Azure or AWS).
• Ability to communicate with non-technical stakeholders.

Responsibilities

• Design, build, and maintain scalable data pipelines and data platform components.
• Develop robust data models and abstractions that enable analytics and reporting.
• Advise clients on data platform strategy and help translate business requirements into sound technical architectures.
• Implement ELT/ETL pipelines and ensure data quality across systems.
• Collaborate with analytics engineers, platform engineers, and infrastructure teams to deliver reliable, end-to-end data solutions.
• Contribute to the design and evolution of modern cloud data platforms.
• Champion engineering quality - testing, documentation, and performance are not afterthoughts here.

Skills

Data engineering

Data modeling

Data platform engineering

SQL

Python

Cloud platforms

Spark / PySpark

dbt

Terraform

CDK

Client-facing

Problem-solving

Tools

dbt

Terraform

CDK

Job description

Devleaps is a boutique data, AI, and technology transformation consultancy based in the Netherlands. We design and implement modern data platforms, analytics foundations, and data governance to unlock data value for clients.

As a Data Engineer at Devleaps you will design scalable data pipelines, develop data models, and collaborate with platform engineers and infrastructure specialists to deliver end-to-end data solutions for diverse clients.