Senior Data Engineer

Jbsfamily; Kuala Lumpur; On-site; MYR 180,000 - 230,000; Full time

Job summary

Jbsfamily is expanding its Data Engineering team in Malaysia. We seek a Senior Data Engineer specializing in Databricks and Snowflake to build scalable lakehouse data platforms for global clients.

You will work with DevOps, Cloud Engineering and Data Scientists in Agile sprints to deliver data solutions across APAC. You will build pipelines with Azure Databricks and PySpark, design data ingestion workflows with Azure Data Factory, and define storage schemas to support AI analytics workloads.

Qualifications

• 6+ years hands-on experience with Databricks on Azure/AWS/GCP, including Spark/ PySpark
• Proficiency in Python/Scala with CI/CD pipelines
• Experience in ETL/ELT design and implementation
• Familiar with Hadoop and Kafka in big data environments
• Passion for building scalable and reliable data systems

Responsibilities

• Build and maintain scalable data pipelines using Databricks and PySpark
• Design and manage data ingestion and orchestration workflows using Azure Data Factory
• Define how data is stored, organized, and accessed
• Design schemas to support AI analytics workloads
• Build real-time analytics platforms, ML-ready data environments, and large-scale reporting
• Establish best practices for data quality, governance and security within Databricks
• Mentor junior data engineers and evolve the team's Databricks expertise
• Drive data architecture and modeling strategy for AI projects
• Implement data anonymization, quality checks, lineage and controls
• Ensure timely delivery of data components aligned with milestones

Skills

Databricks

PySpark

Python

Scala

CI/CD

ETL/ELT

Big data

Hadoop

Kafka

Cloud platforms

Tools

Azure Databricks

Azure Data Factory

Job description

Job Summary:

Our Esteemed and Reputable Client is expanding its Data Engineering Team in Malaysia. They are looking for Senior Data Engineers specialise in Databricks, Snowflake to build scalable Lakehouse data platforms for global Clients. The Senior Data Engineer will work alongside DevOps, Cloud Engineering and Data Scientists in Agile Sprints to deliver data solutions across APAC.

• Build and maintain scalable data pipelines using Azure Databricks and PySpark
• Design and manage data ingestion and orchestration workflows using Azure Data Factory
• Define how data is stored, organized, and accessed
• Design schemas and ensure systems support scalable AI and analytics workloads
• Build real-time customer analytics platforms, ML-ready data environments and large-scale reporting pipelines
• Establish and enforce best practices for data quality, governance and security within the Databricks environment
• Mentor Junior Data Engineers and contribute to evolving the team's Databricks expertise
• Drive the data architecture and modeling strategy for AI projects
• Implement data anonymization, quality checks, lineage and controls
• Ensure timely delivery of data components aligned with project milestones

Requirements:

• Min 6 years hands on experience Databricks on Azure, AWS, or GCP, including Spark (PySpark/Scala),
• Programming experience in Python/Scala, with experience in CI/CD pipelines
• Prior experience in ETL/ELT design and implementation
• Familiar with Big data technologies: Hadoop and Kafka
• Passion for building scalable and reliable data systems