Top Data Engineer Jobs in the Netherlands

Assist design, build, and maintain batch and streaming data pipelines, cloud-based data systems, and data infrastructure for manufacturing plants. Support data modeling, formats, automated deployments, and stakeholder requirements to make manufacturing data accessible for analysis and reporting within a digital product team.

As a Data Engineer, you'll build and enhance scalable big data platforms, working with distributed systems and data processing tools while collaborating with diverse teams.

Build the companys first data stack and data products (internal analytics and customer-facing). Work across data engineering, devops, and software tasks; ship early features, improve developer experience, document proposals, and iterate based on feedback.

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, build, and maintain scalable raw data pipelines for Tencent's overseas games. Optimize ingestion, processing, and storage with upstream engineering; support analysts, data scientists, and ML engineers downstream. Improve pipeline performance, quality, and maintainability using batch and streaming technologies, data modeling, programming, and SQL.

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.

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

The Data Center Engineer will manage data center assets, maintain DCIM documentation, collaborate on deployments, and oversee global operations.

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.

Lead a team of software engineers to design and build a strategic cloud data product on Google Cloud. Engineer solutions, propose improvements, and accelerate customer data solutions. Act as a Google Cloud data engineering expert, mentor teammates, and collaborate with clients in a consulting environment.

Design, develop, and maintain scalable data ingestion, storage, processing, and security solutions. Build and support CI/CD pipelines and production operations (debugging, logs, monitoring). Work with open-source stack (Kafka, Hadoop ecosystem, Docker, Kubernetes) and ensure robust, production-ready software in an agile startup environment while documenting and preventing technical debt.

Design, develop, test, and maintain Informatica-based data integration solutions. Build and support enterprise Data Warehouse and Data Lake platforms, develop and optimize large-scale ETL pipelines, troubleshoot performance and data quality issues, and collaborate with cross-functional teams to deliver scalable data solutions while improving architecture and processing performance.

Design, build, and maintain scalable ETL/ELT pipelines on Azure using ADF, Databricks (PySpark), and Python. Optimize SQL, enforce data quality and monitoring, implement CI/CD with Azure DevOps, and deploy Azure infrastructure via Bicep while ensuring security and governance.

Design and implement scalable Azure data solutions and end-to-end pipelines using Databricks, PySpark/Spark-SQL, ADLS and ADF. Migrate and ingest disparate sources, optimize Spark workloads, support DevOps/ARM deployments, implement serverless functions, manage pipelines, and contribute to governance with Unity Catalog while providing production support and stakeholder collaboration.

Design, build, and maintain scalable Azure data pipelines and ETL workflows using Databricks, Data Factory, PySpark, Python and Airflow. Manage run/ops, monitor performance, resolve incidents, support data governance with Atlas, and create technical documentation and runbooks while collaborating across teams to ensure reliable enterprise data delivery.

Design, build, and maintain scalable Azure-based data pipelines using Databricks and PySpark. Develop ETL/ELT processes, data governance, data quality validations, and lineage tracking. Automate workflows with Python and collaborate with data scientists and stakeholders to deliver reliable datasets for analytics and AI.

Design, build, and maintain scalable data pipelines and ETL/ELT processes using Databricks, Spark, Python, dbt, and Azure Data Factory. Manage and optimize SQL Server workloads, create data models, and develop Power BI reporting. Ensure data quality, integrate multiple sources, support legacy systems (SSIS/SSRS), and collaborate with cross-functional teams.

Design, build, and maintain scalable Azure data platforms and pipelines using Databricks, PySpark, and structured streaming. Implement data lake/warehouse and serverless architectures, data ingestion, transformation, and cleansing workflows. Monitor DevOps pipelines and production workloads, troubleshoot issues, and drive performance, governance, and operational excellence while collaborating with stakeholders and architects.

Design, build, and maintain scalable Azure-based data pipelines and ETL/ELT workflows using Azure Data Factory, Databricks, PySpark, and Python. Implement CI/CD in Azure DevOps, optimize performance, ensure data quality, security, and governance, and collaborate with stakeholders to translate requirements into production-ready data solutions.

Design, develop, and maintain scalable PySpark/Databricks data pipelines. Build and optimize Python data processing workflows, implement orchestration (Airflow preferred), ensure data quality and performance, integrate multiple sources into analytics-ready structures, debug and enhance pipelines, and collaborate in Agile cross-functional teams.

Design, build, and maintain scalable Azure data pipelines using ADF and Databricks. Develop Python-based ETL/ELT processes, ensure data quality, governance, performance optimization, and collaborate with architects and analysts in Agile teams to deploy and monitor enterprise data solutions.

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

Design, build, and maintain scalable ELT data pipelines with Airflow; develop dbt data models and tests; optimize Athena tables/queries and data workflows; provision infrastructure with Terraform; ensure data quality and reliability; collaborate with Analytics, BI, and Engineering; troubleshoot pipeline and data quality issues.

Part-time Logistics Data Engineer (16 hours) consolidates and validates warehouse data, analyzes large datasets to identify trends, bottlenecks, and optimization opportunities, translates insights into recommendations and business impact, improves data quality and governance, supports engineering teams with data intake, and contributes to data models to standardize and improve efficiency across locations.