Top Data Engineer Jobs in the Netherlands

As a Senior Data Engineer, you'll build and manage data pipelines, ensure data quality, and collaborate across teams, contributing to the Data Platform's growth.

Build and maintain high-performance, fault-tolerant distributed backend services and data pipelines for large genomic and health datasets. Design storage, indexing, and async event workflows; optimize latency, throughput, and reliability. Partner with bioinformatics and product teams to validate scientific accuracy and guard AI-driven responses.

Build and operate live pricing data systems and historical replay frameworks, integrate external datasets, optimize performance across C++/Python boundary, and collaborate with traders and researchers to deliver production-quality pricing data pipelines with monitoring and data-quality validation.

Design, build, and operate a scalable data platform for quantitative research and backtesting. Develop production-grade Python applications to ingest, process, validate, and distribute market and reference data. Build automated data pipelines (Airflow, AWS Batch), ensure data quality and observability, and collaborate with researchers, software, and infrastructure teams to accelerate dataset onboarding and research workflows.

Build end-to-end features for a data orchestration platform across Java/Micronaut backend and Vue 3/TypeScript frontend. Implement data-aware orchestration (assets, lineage, freshness, quality), create integrations/plugins (dbt, Fivetran, Airbyte, warehouses), improve UI (flow editor, topology, dashboards), collaborate on 8-week releases, review PRs, and engage with the open-source community.

Design, prototype, and deploy ML and LLM solutions using messy, real-world data. Build data pipelines, models, visualizations and PoCs. Communicate insights to technical and non-technical stakeholders and iterate quickly to deliver business impact.

Design and build highly scalable, low-latency market data systems and APIs. Implement backend services, influence architecture, maintain test coverage, participate in code reviews, troubleshoot incidents, and occasionally be on-call. Work spans streaming and historical market data endpoints and developer-focused API improvements.

Own and evolve the company data platform: build ingestion pipelines into BigQuery, create SQLMesh transformations and dimensional models, improve data quality and observability, manage infrastructure with Terraform and GCP, enable BI and reverse ETL, and set technical direction while mentoring engineers and leading incident response.

Provide expert technical support to ESA on spacecraft on-board computers and data handling across project phases. Develop, verify and validate data handling elements and end-to-end chains, support lab facilities (AI, payload, ADHA/RASTA, CubeSat), run integration and validation campaigns, assist procurement, contribute to R&D roadmaps, and transfer knowledge across ESA. Support CDF activities and participate in reviews and documentation.

Own and evolve a GCP-native data platform from ingestion to reporting. Lead architecture, reliability, observability, data quality, cost optimization, and AI-assisted engineering practices while mentoring engineers and collaborating with product and customer teams.

Design and build governed data pipelines, semantic models, and data products using Databricks, dbt, SQL, and PySpark. Implement Unity Catalog and DataHub governance (lineage, access controls, classification). Collaborate with stakeholders, drive CI/CD, testing, observability, and deliver production-grade analytics and AI-ready data assets.

Design and maintain data infrastructure, build pipelines for data collection, ensure data quality, and collaborate with stakeholders on data requirements.

The Senior Data Engineer will design data architectures, oversee integrations, mentor clients, and ensure adherence to data practices, with a focus on digital marketing.