Top Data Engineer Jobs in Amsterdam

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.

Build and ship full-stack features for a data intelligence SaaS platform, spanning backend services and frontend interfaces. Use AI coding assistants to accelerate development while applying sound engineering judgment. Participate in architecture discussions, code reviews, testing, incident response, troubleshooting, documentation, and knowledge sharing. Partner with product managers to translate requirements into technical solutions. The role emphasizes SaaS architecture, AWS cloud fundamentals, Docker, Kubernetes, CI/CD, agile delivery, autonomy, and production ownership.

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.

Design and optimize Snowflake data models, customer 360 views, identity resolution, segmentation, and CDP-ready schemas. Build pipelines syncing customer data to Braze, Hightouch, and related platforms. Improve performance, cost efficiency, data quality, governance, consent management, and audience activation while collaborating with CRM, marketing, analytics, and technical stakeholders.

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.

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.

Build and maintain Camunda 8 backend data-layer services across relational databases and Elasticsearch/OpenSearch. Design scalable storage, query, retention, streaming, and secondary-storage solutions; investigate production data issues; improve performance and operability; and deliver engineering initiatives collaboratively with Product, QA, Support, and SRE. Participate in L3 support and on-call rotations.

Lead mechanical due diligence and feasibility for data center sites and deals. Validate cooling topology and equipment strategy (air, liquid, hybrid), assess capacity, vendor lead times, and integration with budgets and schedules. Define mechanical readiness gates, deliver validated scope to Delivery, coordinate with stakeholders and vendors, and help build repeatable evaluation standards for AI/hyperscale infrastructure acquisitions.

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 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.

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.

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.

Customer-embedded Principal Data Scientist who leads account-aligned delivery: translate business needs into technical approaches, build and ship production-grade solutions, influence senior stakeholders, prepare transitions to FDE crews, and operate with speed and entrepreneurial ownership to drive sustained business outcomes.

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

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.

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.

Build and operate live pricing data systems and historical replay frameworks, integrate external datasets, optimize performance across C++/Python boundary, and collaborate with traders and researchers to deliver production-quality pricing data pipelines with monitoring and data-quality validation.

Design, build, and operate a scalable data platform for quantitative research and backtesting. Develop production-grade Python applications to ingest, process, validate, and distribute market and reference data. Build automated data pipelines (Airflow, AWS Batch), ensure data quality and observability, and collaborate with researchers, software, and infrastructure teams to accelerate dataset onboarding and research workflows.

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.