Data Platform Engineer

Accenture Southeast Asia; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

Accenture Southeast Asia seeks a Data Platform Engineer to design and deliver scalable infrastructure for training and deploying generative AI models. You will enable data-driven innovation by building high-performance, reliable, and cost-efficient platforms and collaborating with cross-functional teams.

In this role, you will optimize performance and cost across data and AI workloads, evaluate technologies, and contribute to architectural improvements while gaining hands-on experience in data

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field.
• Minimum 1 year of relevant experience in data engineering, platform engineering, or similar roles.
• Intermediate proficiency in Python, with hands-on experience using the Pandas library.
• Intermediate proficiency in Tableau or similar data visualization tools.
• Understanding of data processing, data pipelines, and large-scale data systems.
• Strong analytical and problem-solving skills with attention to detail.
• Ability to work independently and collaboratively in a team environment.

Responsibilities

• Design, build, and implement infrastructure to support large-scale training and inference of generative AI models.
• Optimize platform performance, scalability, and cost efficiency across data and AI workloads.
• Evaluate infrastructure technologies and vendors, providing recommendations aligned with business needs.
• Develop and maintain observability, monitoring, and operational controls for data platforms.
• Collaborate with engineering, analytics, and product teams to deliver robust and scalable AI solutions.
• Support continuous improvement of platform architecture and engineering practices.
• Contribute to technical discussions and problem-solving initiatives across teams.
• Build expertise in data platforms and AI infrastructure through hands-on experience and learning.

Skills

Python

Data analysis

Team collaboration

Problem solving

Education

Bachelor's degree in Computer Science or related field

Tools

Pandas

Tableau

Job description

As a Data Platform Engineer, you will design and deliver scalable infrastructure that supports the training and deployment of generative AI models. This role plays a key part in enabling data-driven innovation by ensuring high-performance, reliable, and cost-efficient platforms. You will collaborate with cross-functional teams to build solutions that drive business impact and accelerate AI adoption.

Key Responsibilities

• Design, build, and implement infrastructure to support large-scale training and inference of generative AI models
• Optimize platform performance, scalability, and cost efficiency across data and AI workloads
• Evaluate infrastructure technologies and vendors, providing recommendations aligned with business needs
• Develop and maintain observability, monitoring, and operational controls for data platforms
• Collaborate with engineering, analytics, and product teams to deliver robust and scalable AI solutions
• Support continuous improvement of platform architecture and engineering practices
• Contribute to technical discussions and problem-solving initiatives across teams
• Build expertise in data platforms and AI infrastructure through hands-on experience and learning

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field
• Minimum 1 year of relevant experience in data engineering, platform engineering, or similar roles
• Intermediate proficiency in Python, with hands-on experience using the Pandas library
• Intermediate proficiency in Tableau or similar data visualization tools
• Understanding of data processing, data pipelines, and large-scale data systems
• Strong analytical and problem-solving skills with attention to detail
• Ability to work independently and collaboratively in a team environment

Preferred Qualifications (Optional)

• Basic knowledge of data architecture and database design principles
• Familiarity with platform engineering concepts and cloud infrastructure
• Exposure to technology architecture planning or roadmap development
• Interest in generative AI technologies and their infrastructure requirements