Senior GCP Data Engineer

16 hours ago

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Xebia

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IT Consultancy • Continuous Delivery • Offshore Services • Deployment Automation • Digital Transformation

5001 - 10000 employees

🏢 Enterprise

🤖 Artificial Intelligence

☁️ SaaS

Description

• Work closely with engineering, product, and data teams to deliver scalable and robust data solutions • Design, build, and maintain data platforms and pipelines and mentor new engineers • Deliver software systems and best practices for scalable and robust solutions • Engineer data platforms for scale, performance, reliability, and security • Integrate data sources and optimize data processing • Proactively address challenges, resolve blockers, and drive effective communication across distributed teams • Continuously seek opportunities to enhance data systems and ensure alignment with evolving business needs.

Requirements

• available to start immediately • 5+ years in a senior developer role with hands-on experience in building data processing pipelines • proficiency with GCP services, especially BigQuery and BigQuery SQL, for large-scale data processing and optimization • extensive experience with Apache Airflow, including DAG creation, triggers, and workflow optimization • knowledge of data partitioning, batch configuration, and performance tuning for terabyte-scale processing • strong Python proficiency, with expertise in modern data libraries and frameworks (e.g., Databricks, Snowflake, Spark, SQL) • experience with unit testing, pre-commit checks, and strict type enforcement for data pipelines • deep understanding of relational and NoSQL databases, data modelling, and data warehousing concepts • excellent command of oral and written English • Work from the European Union region and a work permit are required • Nice to have: expertise in optimizing BigQuery performance using tools like Query Profiler and addressing a compute resource bottlenecks • prior experience developing or testing custom operators in Apache Airflow • familiarity with Docker, Kubernetes, Helm, Terraform, Kafka, and CI/CD pipelines for data environments.