Senior Data Architect

1 day ago


Bangalore, India Rakuten Symphony Full time

Job Title: Senior Data Architect – OSS

Minimum - 10+ years of hands-on experience in data architecture, data modelling, and designing large-scale data platforms.

Location: Bangalore (Onsite)

Why should you choose us?

Rakuten Symphony is a Rakuten Group company, that provides global B2B services for the mobile telco industry and enables next-generation, cloud-based, international mobile services. Building on the technology Rakuten used to launch Japan’s newest mobile network, we are taking our mobile offering global. To support our ambitions to provide an innovative cloud-native telco platform for our customers, Rakuten Symphony is looking to recruit and develop top talent from around the globe. We are looking for individuals to join our team across all functional areas of our business – from sales to engineering, support functions to product development. Let’s build the future of mobile telecommunications together

What Do We Expect From You

As a Senior Data Architect within Product Architecture, you will address the critical challenge of a fragmented data model across our various teams. This pivotal role is responsible for unifying disparate data sources - including telemetry, service graphs, and Root Cause Analysis (RCA) inputs - into a single, coherent, and consistent data model. This foundational work is a prerequisite for advancing our capabilities in Generative AI, comprehensive observability, and robust service assurance, enabling a truly data-driven approach across our product portfolio.

Responsibilities:

Unified Data Model Design & Ownership:

  • Lead the architectural design and implementation of a unified data model that consolidates telemetry, service graphs, RCA, and other critical operational data.
  • Define conceptual, logical, and physical data models that support diverse product needs while ensuring consistency and interoperability.
  • Establish and maintain data architecture standards, principles, and best practices across the product organization.

Data Integration & Pipeline Architecture:

  • Architect scalable and efficient data pipelines for ingesting, transforming, and harmonizing data from various heterogeneous sources.
  • Design robust data integration patterns (e.g., streaming, batch processing) to ensure data availability and freshness for downstream consumers.
  • Ensure data quality, integrity, and security throughout the data lifecycle.

Enabling AI, Observability & Assurance:

  • Ensure the unified data model serves as a foundational prerequisite for GenAI applications, providing clean, contextualized data for training and inference.
  • Design data structures and access patterns that enhance observability capabilities, enabling real-time monitoring, analytics, and alerting.
  • Architect data solutions that power advanced service assurance functionalities, enabling accurate fault correlation, root cause analysis, and performance management.

Data Governance & Lifecycle Management:

  • Collaborate with data governance teams to establish data ownership, definitions, and stewardship across product domains.
  • Define data retention policies, archiving strategies, and data lifecycle management processes.
  • Ensure compliance with data privacy regulations and security best practices.

Technical Leadership & Collaboration

  • Provide senior technical leadership and guidance to engineering teams on data modelling, database technologies, and data architecture best practices.
  • Work closely with other architects (AIML, Observability, Workflow Management), data scientists, and product managers to understand data requirements and deliver impactful solutions.
  • Champion a data-first mindset and promote data literacy across the organization.

Qualifications :

  • 10+ years of hands-on experience in data architecture, data modelling, and designing large-scale data platforms.
  • Proven track record of unifying fragmented data landscapes and building robust, scalable data models for complex domains.
  • Expertise in designing data solutions that support real-time analytics, observability, and machine learning applications.
  • Strong background in architecting data pipelines and integration strategies for high-volume, diverse data sources.

Technical Skills

  • Deep expertise in relational, NoSQL databases (e.g., Cassandra, ClickHouse) and TSDB (e.g., Cortex, VictoriaMetrics, etc.)
  • Strong experience with stream processing technologies (e.g., Kafka, Flink, Spark Streaming) and batch processing (e.g., Apache Spark).
  • Proficient in data modelling techniques (dimensional, relational, graph) and data schema design.
  • Knowledge of data governance frameworks and tools.
  • Proficient in SQL and at least one relevant programming language.

Domain Knowledge

  • Familiarity with telecom operational data, including network telemetry, service topology/graphs, and alarm/event data.

Analytical and Problem-Solving Skills

  • Exceptional analytical skills to identify data relationships, inconsistencies, and design optimal data structures.
  • Strong problem-solving abilities for complex data integration and quality challenges.

Collaboration & Communication

  • Excellent written and verbal communication skills, able to articulate complex data architectural concepts to technical and business stakeholders.
  • Proven ability to collaborate effectively with cross-functional teams, driving consensus on data standards.

Educational Background

  • Bachelor’s degree in Computer Science, Data Science, Information Systems, or a related technical field.

RAKUTEN SHUGI PRINCIPLES :

Our worldwide practices describe specific behaviours that make Rakuten unique and united across the world. We expect Rakuten employees to model these 5 Shugi Principles of Success.

  • Always improve, always advance . Only be satisfied with complete success - Kaizen.
  • Be passionately professional . Take an uncompromising approach to your work and be determined to be the best.
  • Hypothesize - Practice - Validate - Shikumika. Use the Rakuten Cycle to success in unknown territory.
  • Maximize Customer Satisfaction . The greatest satisfaction for workers in a service industry is to see their customers smile.
  • Speed Speed Speed Always be conscious of time. Take charge, set clear goals, and engage your team.


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