Data Engineer

INNOWAVE TECH PTE. LTD.; Singapore; On-site; SGD 60,000 - 80,000; Full time

Job summary

INNOWAVE TECH PTE. LTD. in Singapore is seeking a Data Engineer to establish and lead data infrastructure. This role involves building data systems for AI applications in semiconductor manufacturing.

The successful candidate will develop ETL pipelines, manage datasets, and embed best practices in data governance and security. Applicants must hold a relevant degree and have at least 3 years of experience in data engineering.

Qualifications

• 3+ years of experience in data engineering roles.
• Proven track record of building scalable data systems.
• Familiarity with AI/ML data systems.

Responsibilities

• Build robust pipelines to collect and transform diverse datasets.
• Ensure secure and scalable deployment of data infrastructure.
• Define and enforce best practices in data governance.

Skills

Data pipeline development

ETL frameworks

SQL and NoSQL databases

Python and/or Java

Containerization (Docker)

CI/CD practices

Excellent communication skills

Problem-solving and debugging

Education

Minimum Poly or Bachelor Degree in Computer Science, Engineering, or a related field

Tools

Apache Airflow

Kafka

Data lakes

Data catalog

Docker

Git

Job description

Data Engineer

Roles & Responsibilities

We are seeking Data Engineer to establish and lead our data infrastructure. The successful candidate will be responsible for building our data engineering practice from the ground up, implementing robust data systems for industrial AI applications, and establishing best practices that will power our semiconductor manufacturing AI solutions.

About Innowave Tech Singapore

Innowave Tech is an Artificial Intelligence (AI) company offering solutions for the Semiconductor and Advanced Manufacturing industry. Utilizing deep industrial domain knowledge, proven experience, and innovation, we provide expert AI solutions and systems to address various industry pain points.

CLT Programme Overview

This role is part of a structured Company-Led Training (CLT) Programme designed to accelerate capability development in data engineering, AI, and industrial data applications.

Selected candidates will undergo structured On-the-Job Training (OJT), supported by real-world projects, mentorship, and targeted training courses. Participants will gain hands‑on experience in building data infrastructure, developing ETL pipelines, managing industrial datasets, and supporting AI/ML and LLM applications within advanced manufacturing environments.

This programme equips participants with practical skills in data governance, data platforms, and secure deployment practices to support industrial AI solutions in the semiconductor and advanced manufacturing industries.

Your Role and Impact

As our Data Engineer, you will have a foundational role in building robust data infrastructure to handle manufacturing data and LLM applications, while establishing secure data practices that power our AI solutions for advanced manufacturing operations.

What You’ll Do

1. Select and manage on-premises technologies suitable for secure and efficient operations.
2. Build robust pipelines to collect, clean, and transform diverse datasets including process data, sensor data, image data, and human annotations.
3. Ensure secure, maintainable, and scalable deployment of data infrastructure.
4. Define and enforce best practices in data governance, privacy, and access control.
5. Collaboration & Deployment.

What We’re Looking For

Educational Background:

• Minimum Poly or Bachelor Degree in Computer Science, Engineering, or a related field.
• Only Singaporean, Singapore PR can apply due to project requirements.

Technical Expertise:

• 3+ years of experience in data engineering roles, ideally with on-premises or hybrid infrastructure.
• Proven track record of building scalable data systems from ground up in a startup environment.
• Proficiency in Python and/or Java for data pipeline development.
• Solid experience with ETL frameworks (e.g. Apache Airflow, Dagster) and streaming systems (e.g. Kafka).
• Experience designing and maintaining SQL and NoSQL databases.
• Experience building and operating data lakes and data catalog.
• Familiarity with containerization (Docker), version control (Git), and CI/CD practices.

Soft Skills:

• Excellent communication skills and ability to collaborate with cross‑functional technical and non-technical teams.
• Excellent problem-solving and debugging abilities.
• Ability to balance engineering tradeoffs.

Bonus Skills:

• Experience with manufacturing data systems, especially SPC, SCADA, and industrial sensor protocols (e.g. OPC UA, MQTT, Modbus).
• Familiarity with AI/ML pipelines and tools (e.g. ML flow).
• Knowledge in vector databases and LLM data infrastructure.
• Prior experience working in or with regulated industries (e.g. semiconductor, automotive, aerospace).