Top Data Engineer Jobs in the Netherlands

As a Software Engineer for Speechify, you'll focus on data collection for AI model training, manage cloud infrastructure, develop data ingestion pipelines, and collaborate on dataset roadmaps.

Design and develop cloud-native backend services in Rust to process terabytes of data daily. Build and operate data-intensive microservices on AWS and Kubernetes, integrate with distributed databases and messaging systems (Kafka/RabbitMQ), and collaborate across teams to deliver observability features.

Build and operate large-scale data pipelines and orchestration for generative AI research, focusing on video/audio datasets, feature extraction, labeling, and dataset quality to improve model performance.

The Senior Data Engineer will lead the design and evolution of scalable data architectures, mentor team members, build data pipelines, and integrate Generative AI into workflows.

As a Senior Software Engineer, you'll design and build scalable market data systems, improve API architecture, and enhance overall system performance, contributing to Alpaca's infrastructure for trading financial assets.

The role involves building a scalable data platform for near real-time performance data for eBay's advertising products and collaborating with diverse teams to redefine the advertising space.

Build and maintain a near-real-time data platform that provides advertising performance insights for sellers. Design scalable, highly available systems, deploy continuously, collaborate with designers, product, frontend/backend and ML teams, and contribute to internal open-source projects while mentoring peers and driving technical decisions.

Design, train, and evaluate NLP and LLM-based solutions (RAG, chatbots, extraction, summarization). Curate and preprocess data, build end-to-end model pipelines, fine-tune and evaluate models, and collaborate with stakeholders to deliver clinically impactful generative AI solutions.

The Senior Data Platform Engineer will lead project delivery for data infrastructure, manage near real-time services, and collaborate across teams while contributing to AI and data governance frameworks.

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.

Work with Product and Insurance teams to define KPIs, analyze A/B tests, build and maintain real-time dashboards, contribute to dbt-based data pipelines, and provide data-driven recommendations to influence product roadmap and outcomes.

Provide expert technical support for platform and payload data handling systems across project phases: feasibility, design, simulation, testing, procurement and R&D. Lead resolution of critical development problems, define technology requirements and work plans, manage R&D activities, perform laboratory and hardware verification tasks, monitor technological trends, and contribute to knowledge dissemination and proposal evaluations for ESA projects.

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.

As a Senior Data Engineer at FUGA, you'll manage data pipelines, improve data models, ensure data quality, and collaborate on data-driven solutions.

The Software Engineer will design, build, and operate data integration platforms, ensuring reliable data pipelines, API services, and compliance with data governance regulations.

The Senior Software Engineer will design and build data systems for ingestion, transformation, and delivery, ensuring scalability and compliance. Responsibilities include maintaining data pipeline reliability, mentoring engineers, and contributing to API service designs.

As a Junior Software Engineer, you will build data pipelines, implement API endpoints, ensure data quality, and participate in code reviews within the Data Integration team.

As a Software Engineer in Data Infrastructure, you will collect audio data, enhance the ingestion pipeline, and collaborate with scientists to improve dataset quality and efficiency.

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 operate scalable, near-real-time data pipelines and backend services for a global payments platform. Model transactional ledger data for reconciliation, ensure data quality and observability, and own systems end-to-end in a remote-first environment.

Design, develop, and deploy production-grade ML and AI solutions including LLM fine-tuning, RAG architectures, NLP pipelines, time-series forecasting, supplier risk and anomaly detection, scalable data pipelines, and RESTful integrations with enterprise systems.

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 scalable data pipelines and platforms, lead migration from Snowflake to client service, propose improvements, drive initiatives, and collaborate with senior engineers, product/project managers, and data analysts.

Own and evolve Enode's data platform and pipelines to support the Flex product: build reliable datasets, ensure data quality and monitoring, enable self-serve analytics, and partner with data science on feature pipelines and model readiness. Drive pragmatic platform improvements, documentation, and tooling to scale data reliability and trust across delivery, billing, and reporting.

Lead delivery of end-to-end data and analytics solutions: build dimensional models, develop Power BI dashboards, perform exploratory analysis, design Azure-based data pipelines, capture client requirements, run scenario modelling, test and assure solutions, prepare client communications and lead project teams.