Top Data Engineer Jobs in the Netherlands

The Staff Engineer will define architecture, lead data pipeline design, ensure platform reliability, and mentor engineers, driving data initiatives and technical standards.

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.

Lead the design and delivery of data pipelines and warehouse layers. Mentor team members, ensure data quality, and improve engineering practices. Collaborate with cross-functional teams to enhance healthcare data utilization.

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

Lead design and implementation of client study standards aligned to CDISC (SDTM/ADaM) and regulatory guidance. Provide guidance, training, mentorship, and governance support; partner with statisticians and programmers to build tools and metadata repository solutions; ensure submission readiness and represent IQVIA in industry standards initiatives.

Lead Azure-based data migration activities for applications and COTS platforms. Design and execute ETL processes, migration strategies, SQL scripts, and validation workflows. Analyze source and target structures, identify and remediate data quality issues, and support migration in Agile environments. Collaborate with technical and business stakeholders, troubleshoot migration issues, manage large datasets, and ensure accurate, consistent data transfers throughout the migration lifecycle.

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, deploy, scale and maintain ETL pipelines, Airflow workflows, and data services. Own data quality, optimize storage and query performance, design data models, review and refactor distributed systems, and collaborate with product and cross-functional teams to prioritize and deliver data engineering work.

Own and grow the Data Layer: build and operate ingestion, transformation, reconciliation, and serving pipelines (raw→refined→curated). Use agentic AI tools to accelerate delivery, ensure data correctness, and partner with backend, AI, and product teams to define reliable data contracts.

Own and scale the ingestion pipeline and backend abstractions for high-throughput AI tracing data. Optimize ClickHouse schemas and queries, operate Langfuse Cloud and self-hosted deployments, and build infrastructure-heavy features that enable product engineers to ship data-heavy capabilities.

Design, build, and operate high-frequency, event-driven data pipelines into Snowflake; implement reverse ETL; model data with dbt; deploy cloud infra as code; monitor and improve production reliability, latency, quality, and cost; mentor teammates and establish data engineering standards.

Own and operate the company data platform: build secure, multi-tenant data pipelines and APIs, model and surface data for BI, ensure data quality and compliance (SOC 2, ISO 27001, GDPR), support vector stores and AI retrieval, and drive platform engineering best practices across the org.

Build, maintain, and improve customer data integration APIs and DevOps pipelines for the Customer Data Platform. Design scalable, secure, production-ready APIs using Python and Azure services, implement CI/CD, monitoring, and operational support, collaborate with data and platform teams, and migrate legacy APIs to new standards.

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.

Build and operate the data platform and pipelines to produce trustworthy datasets for billing, reporting, and product decisions. Integrate data across systems, own warehouse data models, implement observability and quality checks, collaborate with stakeholders, and take projects from scoping to production while maintaining infrastructure.

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 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.

Lead infrastructure-as-code and operational ownership for Snowflake and Databricks. Build Terraform modules and CI/CD pipelines, implement observability, manage cost and governance, tune performance (Spark, Delta Lake), and coordinate platform roadmaps with product and FinOps.

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.