IT Data Analyst

Sarawak Oil Palms; Miri; On-site; MYR 48,000 - 60,000; Full time

Job summary

A leading company in the palm oil industry is seeking a Data Analyst to join their team. The successful candidate will work on a greenfield 'Data Transformation' project, engaging in the full development lifecycle of data-related implementations. This role requires strong analytical skills and the ability to work collaboratively with various departments to generate insights and improve business processes.

Qualifications

• 2-3 years of experience in data-related roles.
• Certification in R/Python programming is a plus.

Responsibilities

• Collaborate on a greenfield ‘Data Transformation’ project.
• Engage in the full development lifecycle of data-related implementations.
• Support post-implementation activities for ETL processes.

Skills

Analytical Skills

Teamwork

Problem Solving

Education

Degree in Computer Science

Master’s in Data Science

Tools

Python

SQL

R

Power BI

Job description

Qualifications & Requirements

• Possess at least a Degree / Master’s in Computer Science / Data Science / Data Analytics, or a related field
• At least 2 – 3 years of working experience as a Data Analyst, Data Engineer, Data Scientist, or in a similar role
• Familiar with ETL processes and proficient in programming languages for data analysis, such as Python, SQL, or R
• Knowledge of Power BI would be an added advantage
• Certification as an R / Python programmer for data science would also be an added advantage
• Strong analytical skills for generating insights and solving problems
• Ability to work efficiently in a team, require minimal supervision, and demonstrate a structured way of working
• Able to liaise with respective Heads of Departments to communicate analysis results and provide valuable business insights

Responsibilities

• Collaborate on a greenfield ‘Data Transformation’ project, covering new initiatives and system improvements for various business sectors within the company
• Engage in the full development lifecycle of data-related implementations, including user engagement, analysis, design, co-development with IT, testing, and creating data connections for loading into the data warehouse
• Support post-implementation activities, including maintaining and updating ETL processes and visualizing information
• Stay updated with emerging technologies and adopt new tools as applicable