TalPro

Principal Engineer Big Data

  • Job ID: KQLELRIYDI
  • Job Type: Full Time
  • Industry Type: IT Sector
  • Industry Location: Bangalore/Bengaluru
  • Experience: 8-13yrs
  • No. of Positions: 2
  • Salary Range: 20-35 lac
  • Primary Skills: Java Storm Hive Presto Big Data HDFS Kafka
  • Secondary Skills: Flume NO-SQL Spark MPP architecture
  • Job Location: Bangalore/Bengaluru
  • Posted Date: 5 days ago
Job Description

Roles and Responsibilities

What You'll Do

 

  • End-to-end architecture of Analytics platform that is used to develop, deploy and deliver real-time insights on extremely high-volume of telecom network data
  • Ensuring optimal performance and resource utilization in production environments for a diverse deployment configuration
  • Collaborate with product managers and other stakeholders to understand current and future requirements, research reference architectures and align technology roadmap accordingly
  • Provide guidance to the organization in the form of the proposed architecture, design considerations, proof of concepts, reference implementations and expected RoI for the adoption of new tools and technologies
  • Conduct product-demos and training sessions for delivery teams and customers to streamline upgrade and deployment of new products and releases
  • Mentor junior Platform engineers on code standards and guidelines

 

 

 

Desired Candidate Profile

What Makes You a Great Fit?

 

  • Relevant experience in end-to-end software development and system architecture preferably in a product development organization
  • Hands-on experience in Java and Big Data tech-stack – HDFS, Hive, Presto, Flume, Storm, Kafka, Spark, NO-SQL databases is a must
  • Hands-on experience of working on high-volume and low-latency data Platform for real-time analytics
  • Well familiar with Parallel computing, In-memory computing, cache management, and resource optimization techniques
  • Good understanding of Event-based job orchestration, messaging queues and streaming applications for real-time data processing at scale
  • Understand DevOps principles and work with the team to implement continuous integration and continuous delivery
  • Experience with designing data-platform in any cloud env – AWS, Azure or GCP is a plus
  • Well familiar with data governance concepts and data security tools - Kerberos, Ranger, LDAP, Active Directory
  • ML Ops experience of scaling and deploying ML models in production env is a plus
  • Experience working directly with business clients to design a solution that meets business requirements; ability to clearly articulate pros and cons of various technologies and platforms and architectural options, as well as being able to document use cases, solutions and recommendations.

 

 

 

Perks and Benefits

 

 

 

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