Data Engineer (Snowflake + Databricks + PySpark + Apache)

Data Engineer (Must have experience in Snowflake & Databricks & PySpark & Apache Spark)

Work Location: PJ33, Petaling Jaya (On-site)
Job Type: Permanent, Full-time
Salary: RM9,000 – RM15,000 per month
Working Hours: Monday – Friday, 8:30 AM – 5:30 PM
Occasional evening calls may be required to collaborate with the global team

Open to: Malaysian/ RP-T holder

Job Overview

We are looking for an experienced Data Engineer to join our Data, Analytics & AI team in Malaysia. You will design, develop, and maintain scalable data pipelines and contribute to an enterprise data platform supporting analytics, reporting, data distribution, and AI/ML initiatives.

This is a hands-on role involving modern cloud data technologies, with opportunities to collaborate with global technology teams, data scientists, analysts, and business stakeholders.

Important: Hands-on experience with Snowflake, Databricks, Apache Spark, and PySpark is mandatory.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines for structured, semi-structured, and unstructured data.
• Build data integration pipelines across internal systems, external partners, and cloud platforms.
• Develop ETL/ELT processes to support analytics, reporting, and AI/ML workloads.
• Use Snowflake, Databricks, Apache Spark, and PySpark to process and transform large datasets.
• Develop and enhance data lake and lakehouse platforms, including Delta Lake.
• Build and maintain batch and streaming data pipelines where required.
• Automate data ingestion and transformation workflows using Apache Airflow, Prefect, or equivalent tools.
• Monitor, troubleshoot, and resolve data pipeline, data availability, and data quality issues.
• Optimize pipeline performance, scalability, and processing costs.
• Implement data quality checks and support metadata management, data lineage, and data cataloguing.
• Follow data governance, security, compliance, testing, documentation, and CI/CD best practices.
• Collaborate with global teams and business stakeholders to deliver reliable data solutions.
• Evaluate new technologies and recommend improvements to the data platform.

Job Requirements

• Bachelor's Degree in Computer Science, Information Technology, Engineering, Information Systems, or a related technical discipline.
• At least 3 years of hands-on experience in Data Engineering or a closely related role.
• Strong hands-on experience with all four mandatory technologies:
• Snowflake
• Databricks
• Apache Spark
• PySpark
• Strong programming skills in Python and SQL.
• Solid understanding of ETL/ELT, data modelling, and data warehousing concepts.
• Experience with data lake, lakehouse, or Delta Lake environments.
• Experience with orchestration tools such as Apache Airflow, Prefect, or equivalent.
• Familiarity with cloud platforms, preferably Microsoft Azure.
• Knowledge of data quality, metadata management, or data lineage is an advantage.
• Strong analytical, troubleshooting, and problem-solving skills.
• Good communication skills and the ability to collaborate with technical and business stakeholders.

Salary & Benefits

• Permanent employment opportunity.
• 1.5-month annual bonus.
• Medical coverage, including dental benefits.
• Life insurance coverage.
• Career development and professional growth opportunities.
• Exposure to a global Data, Analytics & AI environment.
• Collaborative working culture with an emphasis on work-life balance.

Occasional evening calls may be required to collaborate with the global team in Poland.

Interview Process

• First Interview: Virtual interview with the Direct Manager
• Second Interview: Face-to-face interview with the Head of Department

How to Apply

Suitable candidates are welcome to submit their latest CV or contact:

Anders Cheong
Talent Acquisition

• WhatsApp: https://wa.me/601117364262
• Email: [email protected]

Please highlight your hands-on experience with Snowflake, Databricks, Apache Spark, PySpark, Python, and SQL in your CV

Pay: RM9,000.00 - RM15,000.00 per month

Work Location: In person