We are seeking a hands-on Azure Databricks Data Engineer to support the implementation of a modern data platform on Microsoft Azure to enable self-serve data analytics for various business users. This role is technical execution-focused, responsible for building data pipelines, implementing structured data layers, and supporting the deployment of Databricks Genie capabilities based on predefined architecture and design.
Job Description
Responsibilities:
- Azure Databricks Platform Implementation
- Develop and maintain data solutions using Azure Databricks (notebooks, Delta Lake)
- Configure and optimize Databricks jobs, clusters, and workloads
- Integrate with Azure Data Lake (ADLS Gen2)
- Databricks Genie Implementation Support
- Support implementation of Databricks Genie based on predefined architecture
- Prepare curated datasets for Genie consumption
- Optimize data structures for query performance
- Data Pipeline Development
- Build ETL/ELT pipelines using Databricks and Azure tools
- Develop ingestion pipelines from APIs, databases, and external systems
- Ensure pipelines are reliable, monitored, and production-ready
- Data Management & Governance
- Apply data quality checks and controls
- Implement access control and data organization practices
- Document pipelines and datasets
- Production Readiness & Optimization
- Ensure scalability and performance
- Optimize queries and pipeline efficiency
- Improve Genie performance to deliver faster, more efficient results
Job requirements:
- Hands-on skills of Azure Databricks (Delta Lake, notebooks), Azure Data Lake (ADLS Gen2), Azure Data Factory or Synapse
- Good SQL and ETL experience and medallion architecture familiarity
- Exposure to Databricks Genie, familiarity with Python/PySpark, Unity Catalog or data governance tools are advantageous
- Good execution focus with the ability to deliver high-quality work independently
- High attention to details, particularly in data quality and accuracy
- Good problem-solving skills, with the ability to troubleshoot data and pipeline issues
- Receptive to feedback and able to iterate quickly based on technical guidance
- Able to collaborate effectively within a technical team environment
Charles, Lau Ngie Hao License No.: 02C3423 Personnel Registration No.: R1656741
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