Data Engineer Intern

1 week ago

Singapore INNOWAVE TECH PTE. LTD. Full time

**About Innowave Tech**:
**Innowave Tech**:M **A**NUFACTURING S **I**MPLIFIED

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.
**Key Responsibilities**:
1. Design and implement multi-tenant data architecture for equipment sensor data.

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

3. Build data quality validation frameworks and metadata management systems.

4. 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

**Screening questions**:

- The intended internship period will be during your course of study?
- Are you students pursuing Computer Science disciplines?
- Are you able to commit for more than 3 months?

**Outcome of Technical Skills and Competencies that Intern will learn**:

- To identify and translate business and technical requirements into data architectures.
- To develop proficiency and practical experience in cloud and on-premises storage solutions.
- To build and maintain data pipelines while documenting technical processes and data flows effectively.
- To gain hands-on experience with tools and system administration for data engineering tasks.
- To collaborate effectively with stakeholders while adapting to new technologies and solving complex data engineering problems within deadlines.

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