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Solution Architect - Big Data Platform

Solution Architect - Big Data Platform

ConfidentialChennai, India
8 days ago
Job description

Role Overview

Seeking an accomplished End-to-End (E2E) Data Architect to lead the design and implementation of large-scale Big Data solutions.

The ideal candidate will combine deep expertise in modern data platforms with proven experience in high-volume, mission-critical telecom or financial services environments.

Prior exposure to the Ericsson Wallet Platform is highly preferred.

Key Responsibilities

  • Define the end-to-end data architecture and data engineering roadmap across Hadoop, Spark, Kudu, HBase, and Impala ecosystems.
  • Design and optimize data ingestion, transformation, storage, and real-time processing pipelines to meet business and regulatory requirements.
  • Collaborate with cross-functional teams (business, analytics, infrastructure, security) to ensure scalability, availability, and performance of the data platform.
  • Establish data governance, metadata management, and best practices for data quality and security.
  • Provide technical leadership, mentoring, and code / design reviews for development teams.
  • Drive PoCs for emerging technologies and recommend architectural improvements.

Primary Skills & Technologies

  • Big Data Platforms : Hadoop, Spark, Kudu, HBase, Impala
  • Data Architecture & Modelling : Enterprise data models, data lakes, real-time and batch processing
  • Cloud & Infrastructure : Experience with hybrid or on-prem big data clusters
  • Preferred : Hands-on exposure to Ericsson Wallet Platform understanding of wallet services, mobile money integrations, and telecom financial 12+ years of IT experience with at least 10+ years in Big Data architecture and solution design.
  • Proven track record of delivering complex, high-availability data solutions in telecom, fintech, or similar high-transaction domains.
  • Strong stakeholder management and excellent communication skills
  • (ref : hirist.tech)

    Skills Required

    Hadoop, Spark, Hbase, Cloud Infrastructure, Impala, Batch Processing

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