Lead Data Engineer (GCP / Kafka / Spark)

The Senior Data Engineer will design, build, and optimize large‑scale data pipelines using Kafka, Spark, and GCP to deliver high‑quality, analytics‑ready datasets. This role requires deep expertise in distributed data processing, data modeling, and cloud technologies, collaborating closely with engineering teams to ensure scalable, reliable, and high‑performance data systems.

Client Details

The client is a highly respected global organization known for driving innovation in advanced technology and large‑scale data solutions. They operate in a fast‑moving environment where cutting‑edge engineering, cloud‑native systems, and high‑impact data platforms play a central role in shaping future products and capabilities.

Description

• Design and build scalable data pipelines for ingesting and processing large datasets using Kafka and Spark.
• Develop and maintain data models and transformation logic to support analytics and reporting in BigQuery.
• Monitor, troubleshoot, and optimize data workflows to ensure performance, reliability, and cost‑efficiency.
• Collaborate with cross‑functional engineering teams to gather requirements and deliver high‑quality data solutions.

Job Offer

• Engage in impactful projects within the technology and telecoms industry.
• Collaborative and professional work environment.
• Comprehensive benefits package!

To apply online please click the 'Apply' button below. For a confidential discussion about this role please contact Serina Miyazono on +81 3 6627 6130.

A successful Senior data Engineer should have:

• Strong expertise in building large‑scale data pipelines with Kafka and Spark (PySpark or Scala).
• Advanced SQL skills and solid experience with data modeling, ETL/ELT processes, and warehousing concepts.
• Hands‑on proficiency with GCP services, especially BigQuery, Dataflow/Dataproc, and Cloud Storage.
• Skilled in Python or Scala, with a strong understanding of CI/CD, version control (Git), and best practices in data engineering.