Top Data Engineer Jobs in Amsterdam

Own production Python data pipelines, ETL/ELT workflows, and the ontology powering an AI platform. Integrate warehouses and business applications with graph databases and vector stores, while managing deployment tooling, cloud infrastructure, monitoring, and security. The role begins as hands-on individual contribution and develops toward technical leadership through mentoring and architecture ownership.

Build and improve Modash’s large-scale creator search system across retrieval, indexing, ranking, embeddings, relevance, and low-latency serving. Own initiatives end to end, from requirements and architecture through implementation, production deployment, measurement, and iteration. Develop multimodal search capabilities using image, video, text, audio, LLMs, and vector search. Collaborate with data, product, customers, and leadership while balancing quality, cost, latency, and reliability.

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.

Lead Netflix’s data health analytics strategy by defining data excellence metrics, building trusted data models and dashboards, analyzing lineage and asset utilization trends, and influencing engineering investments. Partner with platform teams to capture metadata and telemetry, standardize data quality evaluations, and measure improvements in developer productivity, data friction, and tooling adoption.

Build and maintain scalable GCP data pipelines, BigQuery data models, enterprise semantic layers, and CI/CD workflows for a modernized marketing data platform. Rebuild legacy pipelines, support DataHub adoption, enforce data quality, optimize performance and costs, and enable secure multi-brand marketing reporting. Collaborate with product, Martech, analytics, and data engineering teams.

Design, build, deploy, and maintain scalable Databricks data pipelines using Spark, cloud services, and data lake or warehouse technologies. Extract, transform, cleanse, and load data from databases, APIs, and streaming platforms. Implement data models, quality checks, governance, workflow orchestration, and performance optimization. Collaborate with data scientists, analysts, business intelligence teams, and stakeholders to deliver reliable data solutions and support data-driven decision-making.

Develop and improve a Salesforce- and Python-based master data platform supporting product data integration, modeling, validation, enrichment, monitoring, and downstream operations. Responsibilities include designing and testing platform features, improving integrations and workflows, collaborating with operational users, reviewing code, resolving incidents, and participating in occasional on-call support. The role offers growth toward deeper Python development and data platform architecture.

Designs and operates secure, scalable Microsoft Azure infrastructure for enterprise data workloads. Implements Infrastructure as Code with Terraform or Azure Bicep, manages Azure DevOps repositories and CI/CD pipelines, and establishes security, networking, backup, disaster recovery, monitoring, and cost-management practices. The role also supports identity, private connectivity, cloud VM lifecycle management, capacity planning, incident resolution, compliance guardrails, and integrations with internal and external data sources.

Build and own the architecture for Dune’s curated data lifecycle, including dependency-aware orchestration, backfills, schema evolution, retries, recovery, data quality, and alerting. The role combines backend software engineering with large-scale data systems work across Go, Kotlin, Rust, Python, and SQL. Responsibilities include designing ingestion and curation contracts, making architecture decisions, solving ambiguous problems, and leading work that other engineers can execute.

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.

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 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.

Design and build durable, distributed data-streaming infrastructure that decouples process data from Camunda’s live execution engine. Develop customer-facing integrations such as Kafka connectivity, support analytics data consumption at scale, and make architecture decisions around consistency, durability, and storage. Participate in production support and on-call rotations while collaborating with Product, Data Layer, Distributed Systems, QA, SRE, and Support teams. Lead ambiguous, cross-functional engineering initiatives from design through delivery.

Build and maintain Camunda 8 backend data-layer services spanning relational databases and Elasticsearch/OpenSearch. Design scalable storage, query, retention, and streaming systems; improve performance, indexing, and production tooling. Lead engineering initiatives from solution design through delivery, collaborate across teams, provide L3 support, and participate in on-call rotations. Investigate production data issues and contribute to schema evolution, workflow automation, and CI improvements.

Own the design, delivery, and operation of complex data pipelines, datasets, and platform components. Translate business needs into scalable data models and reliable data products, improve data quality and observability, resolve production issues, and establish reusable engineering tools and standards. Collaborate with product and business stakeholders, contribute to architecture decisions, mentor engineers, and participate in on-call support.

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.

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.

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

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.