Senior Data Engineer

Навыки

• Airflow
• Azure
• BigQuery
• CI/CD
• Data Governance
• Data Lake
• Databricks

О компании и продукте

• 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 a Senior 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.

Задачи

• 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
• 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

Требования

• 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

Будет плюсом

• 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

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