About Rakuten:Rakuten India is the Development Centre and key technology hub of the Rakuten Group, Inc. We enable our businesses with our depth of knowledge in multiple streams of technology such as Mobile and Web Development, Web Analytics, Platform Development, Backend Engineering, Data Science, Machine Learning, Artificial Intelligence and much more. Our unique 24/7 support center ensures reliability and sustenance of the Rakuten Ecosystem. With dedicated centres of excellence for Mobile Application Development, Data Analytics, Engineering, DevOps and Information Security, we ensure the success of multiple units of Rakuten Group, Inc. With 1700+ employees and growing, Rakuten India is housed in Crimson House Bangalore in the heart of the city.Our History: In 1997, Rakuten first began with Rakuten Ichiba, a B2B2C marketplace, with just six employees, one server, 13 merchants. With the mission of /"empowering people and society through innovation and entrepreneurship,/" the Rakuten group rapidly grew with regional headquarters across the world.In 2016, Rakuten India opened it doors in Bangalore, India, the tech city known as the Silicon Valley of India! This research and development center became a key technology hub of the Rakuten Group, championing some of the products and platforms that run the businesses. With 1000+ (and growing) Rakutenians working on the very same mission as Rakuten Group, Inc, we believe that technology and business needs must challenge each other for true innovation to rise and make a telling business impact! We have team members who work support Rakuten's global strategy across businesses such as e-Commerce, Digital, Marketing Platforms, Ecosystem Services and so on. /"Walk together/" is our guiding philosophy and together we continue to grow stronger by taking Rakuten’s businesses to the next level with not just existing products but also create some in the relevancy of Artificial Intelligence and Machine Learning.Job SummaryRakuten’s Data Platform Department is looking for a Staff Data Engineer (Platform) to lead the design and evolution of our enterprise data platform on Google Cloud Platform (GCP). This role is a senior individual contributor (IC) position with strong architectural influence, responsible for building scalable, reliable, and high-performance data infrastructure used by multiple engineering, analytics, and machine learning teams.The ideal candidate will combine deep hands-on data engineering expertise with system architecture capabilities, helping define the technical direction of the data platform while building reusable frameworks and platform capabilities that enable teams to build and operate data pipelines efficiently.This role requires strong expertise in GCP-based data ecosystems and large-scale distributed data systems.Key ResponsibilitiesData Platform ArchitectureDesign and evolve the architecture of a scalable enterprise data platform on Google Cloud Platform (GCP).Define architecture patterns for data ingestion, processing, storage, and serving layers supporting both batch and real-time workloads.Design Lakehouse / modern data platform architectures using GCP-native services.Drive architectural decisions around data scalability, reliability, cost optimization, and performance.Establish engineering standards and best practices for data platform development.Platform EngineeringDesign and build reusable data platform capabilities including ingestion frameworks, transformation pipelines, and orchestration patterns.Develop and optimize large-scale ETL/ELT pipelines that process high-volume datasets.Build internal frameworks and tooling to enable self-service data pipelines for engineering and analytics teams.Implement data quality validation, schema management, and automated testing for pipelines.Contribute to the evolution of data platform developer experience.Technical Leadership (IC Role)Act as a technical authority for data platform architecture and engineering practices.Lead design reviews and architectural discussions across multiple engineering teams.Mentor and guide data engineers on distributed data processing, pipeline design, and platform engineering best practices.Drive adoption of standardized frameworks, reusable components, and engineering excellence across teams.Reliability, Observability & GovernanceImplement observability frameworks for data pipelines, including monitoring, logging, and alerting.Build mechanisms for data quality monitoring, lineage tracking, and operational visibility.Ensure implementation of data governance, security, and access control standards.Improve operational maturity through automation, resiliency patterns, and fault-tolerant pipeline designs.Collaboration & Cross-Team ImpactWork closely with data scientists, analytics engineers, product teams, and platform engineers to enable scalable data use cases.Translate complex business and analytical requirements into robust data platform solutions.Act as a technical partner for strategic data initiatives across the organization.Required Skills & ExperienceTechnical Expertise10+ years of experience in Data Engineering, Distributed Systems, or Data Platform Engineering.Strong hands-on experience building large-scale data platforms on Google Cloud Platform (GCP).Deep expertise in GCP data ecosystem, including services such as:BigQueryCloud StorageDataflow / Apache BeamPub/SubDataproc / SparkComposer (Airflow)Strong programming skills in Python, Scala, or Java.Deep understanding of distributed data processing frameworks such as Apache Spark.Experience designing high-volume ETL/ELT data pipelines and streaming data pipelines.Strong experience with data modeling, schema design, and data warehouse architectures.Experience with workflow orchestration frameworks such as Airflow or similar tools.Strong understanding of data reliability, pipeline monitoring, and observability practices.Experience working with large-scale datasets and distributed data systems.Experience optimizing BigQuery cost and performance at scale.Experience with lakehouse technologies (Delta Lake, Iceberg, Hudi).Nice to HaveExperience building self-service data platforms or internal data developer platforms.Exposure to ML platforms, feature stores, or MLOps pipelines.Experience with data catalog, metadata management, and lineage tools.Preferred QualificationsExperience designing enterprise-scale data platforms supporting multiple products and teams.Prior experience in large-scale global data ecosystems.Google Cloud certifications (Professional Data Engineer or Cloud Architect).Background in e-commerce, fintech, or large-scale digital platforms.QualificationsBachelor’s or Master’s degree in Computer Science, Engineering, Data Engineering, or related field.10+ years of experience in data engineering or platform engineering roles.Proven ability to influence technical architecture and engineering practices across teams.Excellent communication and collaboration skills with a strong platform mindset.Passion for building scalable, reliable, and high-impact data platforms.
Job Title
Staff Data Engineer