Data Products Engineer for AI & Self-Service Analytics

Thakral One; Kuala Lumpur; On-site; MYR 180,000 - 240,000; Full time

Job summary

Thakral One is seeking a Data Products Specialist to design and deliver reusable data products for both advanced analytics users and non-technical business users. You will help strengthen self-service analytics, improve data accessibility, and enable data-driven decision-making through scalable data engineering, cloud-based solutions, and reusable data assets.

You will design and build data pipelines, ensure data quality, evaluate new technologies, and collaborate with data scientists,

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Information Systems, or a related field.
• 5 to 10 years of experience in data engineering or data science roles.
• Experience supporting AI/ML model development, feature engineering, and model deployment.

Responsibilities

• Design and build data pipelines and ETL processes from multiple sources to enable data access for stakeholders and AI/analytics needs.
• Ensure high data quality and implement monitoring to detect discrepancies.
• Promote adoption of advanced data visualisation tools for business users and analysts.
• Develop and maintain self-service analytics capabilities across the organisation.
• Collaborate with data scientists, data architects, data analysts, software engineers, and business stakeholders to deliver data solutions.

Skills

Data engineering

Python

SQL

Cloud computing

Education

Bachelor's or Master's in CS/DS/IS

Tools

Power BI

Denodo

OAS

AWS

Azure

GCP

Apache Spark

Job description

Thakral One is seeking a Data Products Specialist to design and deliver reusable data products for both advanced analytics users and non-technical business users. You will help strengthen self-service analytics, improve data accessibility, and enable data-driven decision-making through scalable data engineering, cloud-based solutions, and reusable data assets.

You will design and build data pipelines, ensure data quality, evaluate new technologies, and collaborate with data scientists,