Data Engineer, BSS Platform - BSS Development Department (BSDD)

Job Description:

Business Overview

The Technology Platforms Division (TPD) drives the growth of the Rakuten Ecosystem by delivering innovative, high-quality technology platforms characterized by integrated control and strategic partnerships.

Within TPD, the Telecom Business Application Supervisory Department (TBASD) develops and maintains a unified, high-quality Business Support System (BSS) for Rakuten Mobile. We deliver agile, scalable solutions across the customer lifecycle and continuously enhance system performance through close collaboration with stakeholders.

Department Overview

At BSS Development Department (BSDD), we are managing and evolving the Business Support Systems (BSS) platform, a critical backbone of Rakuten Mobile services. The main functions that BSS provides are: end-customer touchpoints (front-ends, mobile applications for onboarding and for plan management), billing and integration with the core systems of Rakuten Mobile.

Just as Rakuten Mobile has disrupted the mobile industry, we're committed to delivering exceptional value to our business partners and end customers by seamlessly leveraging the wide Rakuten Ecosystem. With a long history of software engineering as a service company providing social infrastructure, we value the speed and quality of our delivery to maximize customer satisfaction.

Our mission is to provide a unified BSS platform that spans across the different business lines of our telecommunication businesses. Having just finished the initial build-up phase of the platform, we are actively looking for talented individuals to make our organization and platforms stronger with teams spanning Japan, India, China, and Singapore.

Position:

Why We Hire

The Business Support Systems Development (BSDD) Department is the core engine behind our company’s telecommunications infrastructure. We develop and operate critical BSS platforms across B2C, B2B, ISP, and Landline services. As we scale to millions of subscribers, our Quality Engineering team is tasked with shifting “Quality” to the left, ensuring that high-velocity releases do not compromise the stability of our mission-critical systems.

Having completed its initial platform build-up phase, BSDD is now focused on scaling, modernizing, and stabilizing the platform for the next phase of growth. Engineering teams are distributed across Japan, India, China, and Singapore, working collaboratively in an English-first environment.

As a Data Engineer in the BSDD, you will design and build the data infrastructure that powers our next-generation telecommunications platform. You will be responsible for architecting high-throughput data pipelines, managing large-scale distributed data lakes, and ensuring the integrity and accessibility of data across our ecosystem. Your work will focus on transforming raw, high-velocity telecommunications events into actionable insights, enabling real-time analytics and supporting mission-critical decision-making for our BSS platform.

Position Details

・Design and implement the data infrastructure that powers our B2B, B2C, and ISP business intelligence

・Build high-performance data pipelines that ingest, transform, and analyze massive volumes of telecommunications data, ensuring the data platform is robust, scalable, and ready for real-time decision-making

・Architect and optimize BigQuery datasets, including partitioning, clustering, materialized views, and complex SQL query tuning for large-scale analytical workloads

・Build and maintain production-grade ETL/ELT pipelines using orchestration frameworks such as Apache Airflow or Google Cloud Dataflow (Apache Beam)

・Develop custom data connectors, micro-transformers, and integration services using Go or Java

・Design efficient data models (star/snowflake schemas) for analytical reporting, including handling nested/repeated structures common in CDR logs

・Integrate real-time streaming telecommunications data using message brokers such as Kafka or Pub/Sub

・Ensure data consistency between operational and analytical layers, working with distributed databases such as YugabyteDB or similar PostgreSQL compatible systems

・Deploy and scale data processing workloads on Kubernetes using containerized services

・Collaborate with product managers, QA engineers, DevOps/SRE, and counterpart engineering teams across global offices to deliver end-to-end data

solutions

Work Environment

・Global distributed team across Japan, India, China, and Singapore

・Agile/Scrum development with two-week sprint cycles

・English as the primary working language for documentation, design discussions, and cross-site communication

・Modern data stack: BigQuery, Kafka/Pub/Sub, Airflow/Dataflow,

containerized on Kubernetes, deployed on cloud infrastructure

・Strong emphasis on engineering craftsmanship: code review culture, automated testing, and continuous delivery

Mandatory Qualifications:

・BigQuery Mastery: Deep understanding of BigQuery architecture, including partitioning, clustering, materialized views, and optimizing complex SQL queries for massive datasets

・Data Pipeline Orchestration: Proven experience building and maintaining production-grade ETL/ELT pipelines using tools like Apache Airflow, Google Cloud Dataflow (Apache Beam), or similar orchestration frameworks

・Programming Proficiency: Strong coding skills in Go (Golang) or Java for building custom data connectors, micro-transformers, and integration services

・Data Modeling: Ability to design efficient schemas for analytical reporting, including star/snowflake schemas and handling nested/repeated data structures common in CDR logs

・Event-Driven Integration: Experience with message brokers (e.g., Kafka, Pub/Sub) for real-time ingestion of streaming telecommunications data

・SQL & Database Literacy: Expert-level SQL skills and experience working with distributed databases (e.g., YugabyteDB or similar PostgreSQL-compatible distributed systems) to ensure data consistency between operational and analytical layers

・Cloud-Native Foundation: Hands-on experience with Kubernetes (K8s) and containerization (Docker) to deploy and scale data processing workloads

・Business Level English (TOEIC 800 or above, or equivalent qualification)

Desired Qualifications:

・Infrastructure as Code (IaC): Proficiency in Terraform or Pulumi for provisioning data infrastructure and BigQuery resources in a reproducible manner

・Streaming Analytics: Experience with real-time stream processing frameworks like Apache Flink or Spark Streaming for sub-second CDR analysis

・Data Governance & Quality: Experience with data cataloging tools (e.g., Data Catalog, Collibra) and implementing automated data quality frameworks (Great Expectations, dbt tests)

・Advanced Telecom Knowledge: Domain expertise in telecommunications billing, charging systems (OCS/CCS), or network protocol analysis (Diameter, GTP, SIP)

・CI/CD for Data: Experience setting up CI/CD pipelines specifically for data projects (e.g., automated SQL linting, schema migration testing, and data regression testing)

・ML Integration: Basic familiarity with BigQuery ML or Vertex AI for predictive analytics on historical CDR patterns (e.g., churn prediction, anomaly detection)

・Experience in agile environments with globally distributed teams

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