Senior Data Engineer

Data Engineering & Platform Development

• 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 Data 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, scalability, security, 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 enforce governance frameworks including:
• Role-Based Access Control (RBAC)
• Attribute-Based Access Control (ABAC)
• Fine-grained data permissions
• Data lineage and auditing
• Configure and manage Data Sharing to support secure external and internal data collaboration.
• Support the adoption and utilization 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 analytics 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 when 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.

Experience

• Bachelor's Degree in Computer Science, Information Technology, Engineering, Data Science, or a related field.
• 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.

Why You’ll Love Working With Us✨

• Up to 24 Days Annual Leave
• Flexible & Hybrid Working
• Performance Bonus
• Enhanced EPF Contributions
• Comprehensive Insurance Coverage
• Training & Development (In-House & External)
• Travel Allowance & Expense Benefits
• Company Trips & Team Events
• Long Service Rewards
• Individual Expenses Benefits

*OKU candidates with physical (mobility-related) disabilities or hearing impairment are encouraged to apply.*