Top Data Engineer Jobs in Amsterdam

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.

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.

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 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.

The Software Engineer will manage data collection for AI model training, enhance ingestion pipelines, and collaborate on dataset roadmaps.

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.

Lead design and delivery of Databricks-based data platform capabilities: build AI-orchestrated data engineering workflows, design semantic data models, implement stable ingestion pipelines, troubleshoot production issues, report and improve data quality, and steward platform improvements across EMEA.

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.

End-to-end delivery of ML-powered services, involving research, prototyping, production, and operations. Collaborate on product requirements while maintaining high quality and operational excellence.

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

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 develop a big-data processing engine and heavy ETL pipelines (including geo-location analysis) across cloud and on-prem. Build distributed, partitioned pipeline architectures using Spark/PySpark, Scala, Airflow, Kubernetes, and cloud platforms; follow Agile, clean-code, and software design best practices while supporting deployments and client-facing interactions.

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.

Lead data and analytics projects: design dimensional models, build Power BI dashboards, run exploratory analysis, capture client requirements, develop end-to-end data pipelines on Azure, test and assure solutions, support client decision-making, and contribute to business generation and people development.

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.