楽天グループ株式会社：1026245　Data Engineer – Data Engineering Section, Analytics & Metrics Department (AMD)

会社名

楽天グループ株式会社

会社概要

未来を信じ、より良い明日を創っていく。
イノベーションを通じて、人々と社会をエンパワーメントする。私たちは、そんな想いを大切に世界の人々に喜びと楽しさを届けます。
楽天は、E コマース、FinTech、デジタルコンテンツ、通信など、70 を超えるサービスを展開し、世界10 億以上のユーザーに利用されています。
これら様々なサービスを、楽天会員を中心としたメンバーシップを軸に有機的に結び付け、他にはない独自の「楽天エコシステム」を形成しています。ダイバーシティ推進は、楽天にとって最優先の企業戦略のひとつです。従業員の出身は70カ国・地域以上。世界中からユニークで多様な文化的背景や視点を持つ優秀な人材が集まり、イノベーションの原動力になっています。社内カフェテリアにはベジタリアン、ハラル対応のメニューを用意。礼拝所（Prayer room）もあります。
また、仕事と育児の両立支援や、障がい者雇用・活躍促進も積極的に推進。社内のLGBT（※1）当事者やアライ（※2）に対して、情報共有やサポート体制の強化も進めています。誰もが自分らしく力を最大限発揮して働ける。それが楽天のダイバーシティです。

70を超えるサービスを提供し、世界30カ国にサービス展開拠点を持ち、従業員の出身国・地域数は100を超え、オープンポジション制度を活用して多様なキャリアを描くことができる点も魅力です。
フレックスタイム制度、事情に応じたリモートワークの活用が可能です。本社には託児所やフィットネスジム、三食無料で利用可能なカフェテリアが併設されるなど、社員を支える環境が整備されています。

ポジション

1026245　Data Engineer - Data Engineering Section, Analytics & Metrics Department (AMD)

仕事内容

Department Overview
As part of the AI & Data Division, we are dedicated to developing "Rakuten Analytics," a powerful analytics platform that supports data-driven decision-making. We contribute to business growth by securely integrating diverse data such as user behavior, purchase history, and location information with Rakuten Group's rich statistical data assets, enabling advanced analysis. Furthermore, as a product development department, we are responsible for the integrated development of everything from data collection to data pipeline construction and the analytics UI.

Position:
Why We Hire
We are seeking a data engineer who can contribute to business growth by strengthening Rakuten Analytics' data analysis pipeline and enhancing data processing through the utilization of new technologies, including AI. We welcome individuals who can leverage their data engineering knowledge and experience to proactively enhance our data analytics infrastructure, and who are also interested in utilizing AI technologies in the process.
　
Position Details
As a Data Engineer, you will build and maintain high-throughput data pipelines that process terabytes of data per hour, enabling rapid data access for users. You will contribute to the entire pipeline lifecycle, from development and deployment to incident response and data quality. Collaborating with the SRE team, you will improve the performance and reliability of our pipeline, leveraging tools like Prometheus and Grafana. You will also work with customer service and product teams to deliver data access solutions that meet diverse customer needs.

Tech Stack
Streaming data processing: Spark, Flink, Dataproc
Batch data processing: Spark, Dataproc
Monitoring and Alerting: Elasticsearch/OpenSearch, Prometheus, Grafana
Data investigations: Python, PySpark, SQL, BigQuery, Hive
CI/CD and automations: Jenkins, Ansible
Programming language: Scala, Java
Pipeline workflow: Airflow, Composer
Cloud service: Google Cloud Platform
　
Work Environment
We Data Engineering Group value collaboration and innovation, and we foster an environment where team members can inspire each other as we build and maintain robust data pipelines. We strive to leverage cutting-edge technologies to address challenges related to data processing, storage, and accessibility, ensuring that reliable and scalable data is available for critical business decisions. In our fast-paced environment, continuous learning and the pursuit of new challenges are encouraged, and you will directly contribute to the data-driven success of the entire organization.

求める経験・スキル

Mandatory Qualifications:
Technical Skills
- 5+ years of hands-on Data Engineering experience in enterprise products (e.g., e-commerce, financial services, telecommunications).
- Proven experience in designing, developing, and deploying streaming and/or batch applications using big data technologies such as Spark, Flink, Kafka, Cloud Pub/Sub, Dataproc, SQL, BigQuery, Cloud Dataflow, Cloud Storage, and Cloud Composer.
- Proficiency in developing Spark applications from the ground up and deploying them to production.
- Ability to understand and modify existing Spark applications to implement new features and resolve bugs.
- Experience in troubleshooting and optimizing Spark application performance through configuration adjustments, JVM tuning, and code refactoring.
- Ability to perform data quality assurance (QA) and investigate data discrepancies using SQL or Spark.

Soft Skills/Competencies
- Strong ownership and a proactive approach to improving our product.
- Logical problem-solving skills and a systematic approach to execution.
- Proven ability to drive initiatives from concept to completion.
- Excellent collaboration and communication skills.
- Ability to work productively and reliably in an asynchronous environment.
　
Desired Qualifications:
- Have worked on developing and optimizing applications that regularly processes data with at least 1TB's in size
- Experience on cloud bigdata technologies like BigQuery, Dataproc, PubSub, etc.
- Working knowledge in DevOps tooling like Jenkins, Ansible, etc.