Data Engineer (AWS)

TL;DR

Data Engineer (AWS/Spark): Designing, building and maintaining the data and analytics infrastructure to support cross-functional product teams and machine learning algorithms with an accent on DataOps and pipeline optimization. Focus on building scalable ELT pipelines, automating data processes, and integrating external data sources via custom APIs.

Location: Hybrid (Amsterdam). Must be a resident of the Netherlands and within commutable distance to the Amsterdam office (minimum 2 days per week onsite).

Company

Edtech platform providing equal access to study resources for millions of students across 120,000 institutions worldwide.

What you will do

• Support DataOps by optimizing and maintaining data pipelines and automating key processes.
• Build and refine data pipelines and resolve pipeline incidents.
• Integrate new external data sources through custom APIs and pipelines.
• Collaborate with DevOps to monitor and troubleshoot data systems and contribute to documentation.
• Collaborate with Data Scientists, Analysts, and Product Managers to provide support for ad hoc data requirements.

Requirements

• 3+ years of experience in data engineering.
• Proficiency in SQL and at least one scripting language (Python, Java, or Scala).
• Experience with data orchestration tools such as Airflow.
• Understanding of the ELT paradigm and tools like dbt.
• Knowledge of AWS cloud technologies and distributed computing systems (Spark).
• Familiarity with Infrastructure as Code using Terraform.

Culture & Benefits

• Hybrid working policy with a modern office in central Amsterdam.
• Comprehensive financial perks including a pension scheme and SAR equity scheme.
• Learning & Development budget of 2,500 Euros per year and a WFH set-up budget of 800 Euros.
• Free office lunch prepared by a chef, coffee, tea, and snacks.
• 24 holiday days with options to buy additional leave and work abroad for 4 weeks.
• Extra perks: free in-house Dutch lessons, Travel Card (NS Business), and annual company trips.