Data Engineering Lead

Situated in the heart of Singapore's Central Business District, Rakuten Asia Pte. Ltd. is Rakuten's Asia Regional headquarters. Established in August 2012 as part of Rakuten's global expansion strategy, Rakuten Asia comprises various businesses that provide essential value-added services to Rakuten's global ecosystem. Through advertisement product development, product strategy, and data management, among others, Rakuten Asia is strengthening Rakuten Group's core competencies to take the lead in an increasingly digitalized world.

Department Overview

The Data Lake house Section provides the foundation for Rakuten Digital Twin strategy enabling seamless, real-time understanding of customers across services. 
We manage one of the world's largest first-party datasets, developing and operating products like Customer DNA (CDNA) and Deep CDNA, which unify data across business units. 

As a Senior Data Engineer, you will play a key role in the architecture, development, and optimization of Rakuten's core data platform. 
You will lead engineering efforts to design scalable, reliable, and secure data pipelines and collaborate closely with global teams in Japan and India.

Responsibilities:

- Lead the design, development, and operation of scalable and reliable data pipelines supporting Customer DNA and related data products.
   
- Drive best practices in data engineering, including performance tuning, automation, and observability.
   
- Collaborate with product managers, data scientists, and analytics engineers to deliver end-to-end solutions.
   
- Oversee data ingestion, transformation, and quality control processes to ensure trusted data availability.
   
- Design and optimize data architectures leveraging Google Cloud Platform(GCP) services (e.g., Big Query, Dataflow, Pub/Sub, Cloud Storage).
   
- Mentor team members, promote engineering excellence, and contribute to a culture of learning and collaboration.
   
- Ensure compliance with data governance, security, and privacy standards across systems.
   
Qualifications:

- 5+ years of experience building and operating big data platforms for analytics or business operations.
   
- 2+ years of experience managing large-scale, real-time or unstructured datasystems in distributed environments.
   
- Proficiency in Python programming and related libraries (e.g., Pandas, NumPy, PySpark, Pydantic).
   
- Strong hands-on experience with Google Cloud Platform (GCP), including Big Query, Cloud Storage, Cloud Functions, Dataflow, Pub/Sub, and IAM.
   
- Experience with Infrastructure-as-Code (IaC), CI/CD pipelines, and cloud resource management.
   
- Experience with **containerization (Docker)** and **orchestration (Kubernetes)** in cloud-native environments.
   
- Strong understanding of **SQL and NoSQL** data stores, with experience inlarge-scale distributed systems.
   
- Proven ability to identify and solve complex data engineering challenges, ensuring system reliability and scalability.
   
- Excellent communication and leadership skills, with experience guidingcross-functional or remote teams.
   
- Business-level proficiency in English.

Good to have:

- Experience designing Python-based data engineering frameworks ensuring scalability, performance, and maintainability.
   
- Experience developing and maintaining reusable Python packages and libraries for data pipelines.
   
- Familiarity with API-based data integration and micro service architectures.
   
- Experience implementing cloud-native data solutions to optimize cost and performance.
   
- Proven ability to balance hands-on technical contribution with strategic leadership.
   
- Ability to mentor engineers and promote best practices in software craftsmanship.
   
Rakuten is an equal opportunities employer and welcomes applications regardless of sex, marital status, ethnic origin, sexual orientation, religious belief, or age.