Senior Data Engineer

At Sytac, we build high-performing engineering teams for leading organizations in the Netherlands and beyond. We combine a pragmatic, people-first culture with strong technical craftsmanship, giving engineers autonomy in real production environments, backed by a consultancy that invests in growth, community, and long-term partnerships.

For one of our enterprise clients in a data-intensive domain, we are looking for aSenior Data Engineer to help build and maintain scalable, reliable, and production ready data pipelines. You’ll work on batch and streaming data products that power analytics, reporting, and AI/ML use cases across the organization.

This is a high-impact role requiring deep expertise in modern lakehouse architectures, cloud-native data tooling, and robust engineering practices focused on reliability and ownership.

What you’ll do

• Design, build, and operate end-to-end data pipelines across Azure (ADF/Databricks) or GCP (Dataflow/BigQuery).
• Implement lakehouse patterns (Delta Lake, medallion architecture) for scalable and reliable data products.
• Deliver batch and streaming pipelines using technologies such as Kafka, Pub/Sub, or Event Hubs.
• Write high-quality, production-grade code in Python and SQL to process and transform large datasets.
• Apply strong engineering principles to data modelling, quality, lineage, and governance.
• Set up CI/CD workflows for data pipelines and infrastructure to ensure reproducibility and automation.
• Implement monitoring and observability to ensure the health and reliability of data systems.
• Optimize performance and cost across compute, storage, and orchestration layers.
• Collaborate with stakeholders, including Data Scientists and ML Engineers, to translate business needs into technical solutions.
• Contribute to data engineering standards and mentor the team on best practices.

What we’re looking for

• 5+ years of experience as a Data Engineer in complex cloud environments.
• Strong background in Azure(ADF, Databricks)or GCP (Dataflow, BigQuery).
• Expertise in Python and SQL for complex data processing and validation.
• Deep understanding of Lakehouse concepts: Delta Lake, curated layers, and medallion architecture.
• Hands-on experience with streaming (Kafka, Pub/Sub, Event Hubs) and batch processing.
• Solid grasp of DevOps for Data: CI/CD, testing automation, and deployment pipelines.
• Infrastructure awareness: Experience with Terraform or IaC is required for this senior level.
• Proactive mindset: Ability to work closely with cross-functional teams in a regulated or enterprise setting.
• Fluent in English + EU residency (no sponsorship).

Tooling (must use in practice): Python, SQL, Spark (Databricks), Azure Data Factory / GCP Dataflow, Kafka/Event Hubs, Terraform, CI/CD (GitLab/GitHub Actions), Airflow or similar orchestratrs.

Nice to have

• Affinity with AI/ML: Experience delivering feature-ready datasets for training and inference.
• MLOps exposure: Understanding of dataset versioning and feature stores.
• Data Governance: Experience with tools for data lineage and cataloging.