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  4. Click Websites.
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Jobs or company...

Data Engineer Intern (Equipment Health Analytics) Intern (INNOWAVE TECH PTE. LTD.) – Central Region, Paya Lebar

Salary undisclosed
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Roles & Responsibilities

About Innowave Tech

Innowave Tech is a leading AI solution provider in the semiconductor industry, specializing in developing cutting-edge technologies for innovation and efficiency. Our focus is on computer vision and large-scale data analytics to meet the complex needs of our clients in the advanced manufacturing and semiconductor industry.

Job Description:
As a Data Engineer Intern (Equipment Health Analytics), you will develop data architecture and infrastructure for industrial IoT data. You will collaborate with cross-functional teams to build and maintain scalable and reliable data storage and data pipeline. This role offers a unique opportunity to work with innovative technologies and make a meaningful impact in a fast-evolving industry and is ideal for candidates with strong data engineering skills and interest in AI applications.

Key Responsibilities:

• Design and implement multi-tenant data architecture for equipment sensor data.

• Implement and maintain storage solutions across cloud and on-premises systems.

• Build data quality validation frameworks and metadata management systems.

• Document technical processes and data flows.

Requirements / Qualifications:

• Minimum Poly, Bachelor’s, or Master’s degree in Data Engineering, Computer Science, or related field.

• Self-motivated learner who quickly adapts to new tools and technologies.

• Strong problem solver with proven ability to complete complex tasks.

• Detail-oriented with high standards for work quality.

• Excellent communicator and team collaborator.

• Internship duration should be at least 3 months full time.

• Resume should indicate your forecasted internship dates.

Required Skill Sets:

• Python programming

• SQL and NoSQL databases

• Message queues or Redis

• Storage solutions: Cloud (Azure Blob, AWS S3) or On-premises (Ceph, MinIO)

• Data lake concepts and implementations

• Linux shell scripting and system administration

Knowledge of the following is a plus:

- IoT data and manufacturing processes

- Basic understanding of data security principles

- Familiarity with DevOps practices
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