Senior Data Engineer
Summary
Senior data engineer in Kuala Lumpur who designs, builds, and maintains Databricks-based data pipelines, lakehouse, and enterprise data warehouse solutions using PySpark, Delta Lake, Unity Catalog, and CI/CD with GitHub Actions, plus a rotating production support roster.
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:
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
Experience
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
Databricks Workflows
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
Infrastructure-as-Code (Terraform preferred)
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.
Unlock job insights
Hirer responsiveness Salary match Number of applicants
Computer Software & Networking 101-1,000 employees
Software International Corporation (M) Sdn Bhd (SI), established in 1995, was one of Malaysia’s first MSC-status IT service providers. SI delivers Infrastructure Management and Application System Solutions across industries such as Insurance, Telco, Construction, Data Centers, and Government. A joint venture with a Global Fortune 100 Financial Services Company in 1998 strengthened its global capabilities. Today, SI serves diversified worldwide clients, including long-term Fortune 100 partners.
Software International Corporation (M) Sdn Bhd (SI), established in 1995, was one of Malaysia’s first MSC-status IT service providers. SI delivers Infrastructure Management and Application System Solutions across industries such as Insurance, Telco, Construction, Data Centers, and Government. A joint venture with a Global Fortune 100 Financial Services Company in 1998 strengthened its global capabilities. Today, SI serves diversified worldwide clients, including long-term Fortune 100 partners.
Skills
- AI
- Analytics
- Automation
- AWS
- Azure
- CI/CD
- Cloud
- Data Engineering
- Data Governance
- Data Lineage
- Data Modeling
- Data Pipelines
- Data Quality
- Data Science
- Data Warehousing
- Databricks
- Delta Lake
- Design Patterns
- DevOps
- ELT
- ETL
- GCP
- Git
- GitHub
- GitHub Actions
- Infrastructure as Code
- Lakehouse
- Machine Learning
- Networking
- Observability
- Power BI
- PySpark
- RBAC
- Sdn
- Snowflake
- SQL
- Stakeholder Management
- Tableau
- Terraform
- Unity