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MSCI Associate Data Engineer Job | 3–5 Years Experience | Apply Now – Pune, India

Yogi Siddeswara 0

Position: Associate Data Engineer

Company Name: MSCI Inc

Website: MSCI

Wikipedia: MSCI Wiki

Degree Needed: B.E/B.Tech

Batch Eligible: 2020/2021/2022/2023/2024

Work Location: Pune, India

Experience Level: 3 – 5 Years

Salary: Best In Industry

Job Description:

Join MSCI as an Associate Data Engineer in Pune. You’ll work on building robust, scalable systems that support our AI initiatives and data operations. As part of the AI Team, you will be involved in developing data processing pipelines, optimizing system performance, and contributing to distributed systems that handle vast amounts of data. Your role will be crucial in ensuring data consistency across distributed nodes and integrating machine learning models into workflows.

Skills & Experience:

  • Bachelor’s degree in Computer Science or related field
  • 3–5 years of experience in software engineering or data engineering
  • Proficiency in Python and strong software engineering skills
  • Understanding of batch and real-time data processing concepts
  • Experience with cloud technologies and distributed systems
  • Interest in data analytics and machine learning pipelines
  • Strong problem-solving and analytical abilities

Key Responsibilities:

  • Assist in designing and implementing scalable distributed systems
  • Develop and optimize data processing pipelines for large datasets
  • Contribute to system performance improvements and error handling mechanisms
  • Work with AI specialists and product managers to implement AI-adjacent solutions
  • Help integrate machine learning models into data workflows

How to Apply:

If you meet the qualifications and are ready for this exciting opportunity, apply directly via the official MSCI job portal:

Interview Tips for MSCI:

  • Be prepared to demonstrate your knowledge of Python and distributed systems
  • Showcase your experience in handling large datasets and cloud technologies
  • Prepare for discussions on system scalability and data consistency across distributed systems

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