Top Data Engineer Jobs in the Netherlands

Design, build, and maintain large-scale data environments and reusable ETL pipelines. Collect and transform data from multiple sources, develop integration services in cloud or hybrid infrastructures, and apply orchestration, API development, and ML/AI knowledge to ensure high-performance, production-ready datasets.

Build, operate, and improve Azure-based data pipelines integrating SAP S/4HANA and other systems. Design and optimize Azure SQL databases, develop ADF pipelines, handle daily operations and incident tickets, support ad hoc data requests, implement CI/CD with Azure DevOps and Git, consume REST APIs, and document solutions while modernizing legacy processes.

Design, develop, and maintain scalable data pipelines and processing workflows using Databricks, PySpark, Azure Data Factory, and Python. Implement data governance, quality, and lineage practices. Optimize and troubleshoot pipelines to ensure reliable, enterprise-grade data delivery.

Design and build scalable ELT pipelines and curated data models on a Databricks Lakehouse. Partner with business teams to create reliable data products, implement governance and quality checks, and enable BI and self-service analytics while contributing to platform best practices.

Own and evolve BlockTech’s self-hosted data infrastructure for trading systems, including low-latency ingestion, Kafka and NATS streaming, PostgreSQL, ClickHouse, and Iceberg storage. Ensure data reliability through gap detection, repair, schema evolution, capacity planning, and failure handling. Partner with trading and research teams, lead projects from concept through production, establish technical standards, mentor engineers, and influence platform architecture.

The role involves designing and maintaining cloud-native data pipelines, implementing medallion architecture, and ensuring data quality in a collaborative environment.

Supports the design, installation, qualification, administration, security, compliance, and lifecycle management of AVEVA PI Data Historian and other automation data systems at a pharmaceutical manufacturing site. Partners with automation, IT, facilities, and information security teams; develops procedures; performs audits; maintains data integrity; and supports manufacturing teams as systems expand. The role is fully onsite and begins as a 12-month contract with potential conversion to permanent employment.

As a Data Analyst, you'll analyze user behavior and product performance, create reports and dashboards, and collaborate with teams to drive data-informed decisions.

Own end-to-end AI-automated data platform migration projects (1-4 concurrently): scope, plan, execute, and hand off. Act as primary customer contact, configure Datafold's Migration Agent, partner with engineering on execution, and help refine delivery playbooks.

Own and evolve a cloud-agnostic data and ML platform supporting ingestion, storage, processing, model training, deployment, and lifecycle management. Build reliable, scalable, automated infrastructure using DevOps and MLOps practices, including CI/CD, Infrastructure-as-Code, containerization, monitoring, governance, security, and cost optimization. Collaborate with data science, ML engineering, and IT teams while maintaining vendor-delivered components, documentation, and operational processes.

The Principal Data Engineer will improve data pipeline architecture, optimize data flows, and support data projects for various teams in the company.

Design, implement, and maintain data lakehouse solutions on AWS (S3, Glue, Lake Formation, Athena, Redshift) using Databricks/Delta Lake or similar. Build secure, compliant data pipelines focusing on PII protection and data residency. Advise and manage client stakeholders, collaborate with cross-functional teams, and support ML feature stores and model deployment.

Design and maintain data warehouse systems, develop ETL pipelines, manage datasets for analytics, and implement real-time data solutions.

Own and operate all PostgreSQL databases across BSS/OSS/NOC and network elements. Build backup/DR, performance tuning, bulk-data pipelines, monitoring (Prometheus/Grafana), HA patterns, schema reviews, data governance (retention, masking), and runbooks. Implement cross-platform integration with vendor network databases and automate bulk loads, migrations, and purges.

The role involves creating and automating infrastructure features for data platforms using Python, with a focus on distributed systems and collaboration within a global team.

The role involves automating OpenSearch operations by developing features in Python, collaborating with an international team, and providing expertise on data platforms.

As a Software Engineer on the data platform team, you'll automate data platform operations, write Python code, and collaborate on solutions within a distributed team.

Design and implement core YTsaurus functionality in C++, build and evolve platform-level capabilities, improve APIs and UX for internal users, own production quality including incident response/on-call, and collaborate with stakeholders to prioritize and deliver scalable data platform features.

Join Zencore as a Senior Data Engineer, leveraging Google Cloud expertise and technology strategies to assist clients with data and application modernization.

Build and operate shared AI platform infrastructure for LLM applications, agents, RAG, tool calling, and AI workflows. Develop data and knowledge pipelines, secure enterprise integrations, reusable frameworks, deployment and observability standards, and developer tooling. Take AI systems from experimentation to reliable production while ensuring security, privacy, governance, scalability, quality, and cost efficiency. Collaborate across Engineering, Product, and IT to establish practical AI platform patterns and guardrails.

Design and scale mission-critical market data services for stocks, options, crypto, and foreign exchange. Responsibilities include architecting backend systems and APIs, maintaining software quality and test coverage, participating in code reviews, and troubleshooting incidents and bugs. The role uses Go and Python with REST, gRPC, WebSockets, SSE, Docker, Kubernetes, Google Cloud, BigTable, Prometheus, Grafana, and ELK.

Design, build, and scale high-performance data pipelines and infrastructure (ingestion, transformation, storage, modeling, serving) using ClickHouse, Postgres, Python and dbt. Manage data quality, reliability, and observability at terabyte and 500M+ address scale, collaborate with researchers and product, mentor engineers, and leverage AI tools to accelerate work.

Build and maintain enterprise data platform and ETL/ELT pipelines, design and deploy data models, ensure data quality and governance, integrate third-party sources, and support analytics and AI initiatives across the organization.

Own and evolve the core data platform: warehouse design, dbt transformations, and production AWS pipelines. Refactor and harden API-driven data flows, ensure observability and testing, partner with backend and product teams, and contribute to data-aware backend features to deliver reliable, product-focused data.

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.