Data Engineer

Esync Software Services; Kuala Lumpur; On-site; MYR 180,000 - 260,000; Full time

Job summary

Jora Malaysia is seeking an experienced Data Engineer to design, build, and optimize scalable data pipelines and data products using Databricks and PySpark. You will shape enterprise DW/Lakehouse solutions supporting analytics, AI/ML use cases, and ensure data quality, security, and performance.

The role requires 4+ years in Databricks within enterprise contexts, strong governance experience with Unity Catalog, and expertise in dimensional modeling and ETL/ELT design.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field.
• 5–8 years of experience in Data Engineering, Data Warehousing, or Big Data technologies.
• Minimum 4+ years of hands-on Databricks experience in enterprise environments.
• Experience designing and implementing enterprise Data Warehouse solutions and modern Lakehouse architectures.

Responsibilities

• Design, develop, and maintain scalable data pipelines and data products using Databricks and PySpark.
• Build and optimize ETL/ELT solutions supporting batch and near real-time data processing.
• Design, develop, and maintain enterprise Data Warehouse and Lakehouse solutions that support reporting, analytics, and AI/ML use cases.
• Develop and maintain enterprise data models using Delta Lake and Delta Tables.
• Design and implement dimensional data models, including Fact and Dimension tables, Star Schema, Snowflake Schema, and SCD.
• Ensure data quality, reliability, scalability, and performance across the data platform.
• Implement best practices for code management, testing, deployment, and operational monitoring.
• Design and maintain governance frameworks utilizing Unity Catalog, RBAC, ABAC, and data lineage.

Skills

PySpark

Databricks

Delta Lake

Unity Catalog

RBAC

ABAC

GitHub

CI/CD

SQL

Cloud platforms

Education

Bachelor's degree in CS/IT/Engineering

Tools

Power BI

Tableau

GitHub Actions

Job description

Jora Malaysia will close on 9th September 2026. Thank you for being with us, we are cheering you on as you continue your career journey.

Responsibilities

• Design, develop, and maintain scalable data pipelines and data products using Databricks and PySpark.
• Build and optimize ETL/ELT solutions supporting batch and near real-time data processing.
• Design, develop, and maintain enterprise Data Warehouse and Lakehouse solutions that support reporting, analytics, and AI/ML use cases.
• Develop and maintain enterprise data models using Delta Lake and Delta Tables.
• Design and implement dimensional data models, including Fact and Dimension tables, Star Schema, Snowflake Schema, and Slowly Changing Dimensions (SCD).
• Ensure data quality, reliability, scalability, and performance across the data platform.
• Implement best practices for code management, testing, deployment, and operational monitoring

Databricks Platform & Governance

• Implement and manage Unity Catalog for centralized governance, data discovery, and security.
• Design and maintain governance frameworks utilizing:
• Role-Based Access Control (RBAC)
• Attribute-Based Access Control (ABAC)
• Fine-grained data permissions
• Data lineage and auditing
• Configure and manage Delta Sharing to support secure external and internal data collaboration.
• Support adoption and administration of Databricks Genie, including:
• Natural language data interaction capabilities
• Security and access governance controls

Performance Optimization

• Perform advanced PySpark performance tuning and troubleshooting.
• Optimize query performance, cluster utilization, partitioning strategies, and workload management.
• Identify bottlenecks and proactively improve platform efficiency and cost optimization.
• Optimize Data Warehouse and Lakehouse workloads to support high-performance reporting and analytical processing.

DevOps & Automation

• Design and implement CI/CD pipelines for Databricks solutions.
• Integrate Databricks development lifecycle with GitHub, GitHub Actions, and enterprise DevOps processes.
• Automate deployment, testing, code validation, and release management processes.
• Establish infrastructure and data engineering best practices.

Stakeholder Management

• Engage with business users, data consumers, architects, analysts, and technology leadership to gather requirements and deliver data solutions.
• Translate business requirements into scalable technical designs, data models, and platform capabilities.
• Communicate effectively with stakeholders across multiple organizational levels.
• Work independently while managing priorities and ensuring timely delivery of commitments.
• Provide technical guidance and mentorship to junior team members where required.

Production Support

• Participate in a rotating production support roster.
• Troubleshoot production incidents and prioritize issue resolution within established SLA requirements.
• Conduct root cause analysis and implement preventive measures.
• Ensure platform stability, reliability, and operational excellence.

Required Qualifications

• Bachelor's Degree in Computer Science, Information Technology, Engineering, Data Science, or a related field.
• 5-8 years of experience in Data Engineering, Data Warehousing, or Big Data technologies.
• Minimum 4+ years of hands‑on Databricks experience in enterprise environments.
• Experience designing and implementing enterprise Data Warehouse solutions and modern Lakehouse architectures.

Technical Skills

Strong experience in:

• PySpark development and optimization
• Delta Lake and Delta Tables
• Unity Catalog
• RBAC and ABAC implementation within Unity Catalog
• GitHub and Git-based development workflows
• CI/CD implementation using GitHub Actions or equivalent
• SQL and advanced query optimization
• Cloud platforms (Azure, AWS, or GCP)
• Data security, governance, and compliance frameworks
• Enterprise Data Warehouse architecture and implementation
• Dimensional data modeling (Star Schema and Snowflake Schema)
• Fact and Dimension modeling
• Slowly Changing Dimensions (SCD Type 1 & Type 2)
• Data Warehouse performance tuning and optimization

Additional Technical Knowledge

• Data warehouse concepts and methodologies
• Lakehouse architecture and Medallion design patterns
• Data observability and monitoring

Soft Skills

• Strong ownership mindset with high accountability and commitment to delivery.
• Ability to work independently with minimal supervision.
• Excellent analytical and problem-solving skills.
• Strong communication and stakeholder management capabilities.
• Ability to work effectively with stakeholders across business and technical functions.
• Ability to manage multiple priorities in a fast-paced environment.
• Collaborative team player with a proactive and customer-focused attitude.
• Willingness to participate in production support and on‑call rotation schedules.

Preferred Qualifications

• Databricks Certified Data Engineer Associate or Professional certification.
• Experience implementing enterprise data governance frameworks.
• Experience supporting large-scale Lakehouse and Data Warehouse architectures.
• Experience working with regulated industries and compliance requirements.
• Knowledge of Data Mesh and modern data platform architectures.
• Experience integrating Databricks with Power BI, Tableau, or other BI and analytics platforms

Success Factors

The successful candidate will:

• Be the go-to Databricks engineering expert within the team.
• Drive governance and security best practices through Unity Catalog.
• Deliver reliable, scalable, and high-performing data solutions and enterprise data warehouse platforms.
• Partner effectively with business and technical stakeholders.
• Demonstrate strong ownership, accountability, and operational excellence.
• Contribute to continuous improvement of the organization's modern data platform capabilities.